Hi everyone,
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In 1994,scientists used a robot named DANTE-II to monitor volcanic activity in Alaska's Mount Spurr.the spider-like robot was controlled by commands sent by satellite from Anchorage,many miles away.DANTE-II's mission was to creep up to the edge of the volcano which had errupted in 1992 &1993 and peer over volcano's edge to transmit images to scientists.DANTE-II used a laser imaging system and a camcorder to transmit images to satellites.these images were then forwarded by satellite to Anchorage and Ames Research Center(CALIFORNIA).

Robots have also been used to study underwater enviornments.oceanographers used a robot,compuers communication techniques to explore GULF of CALIFORNIA.the robot was controlled by a nearby ship.

Robots have also been used in Space Exploration Missions.eg PATHFINDER.
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RECENTLY:
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these are several experimental robots already being used successfully:
1.)"AIBO" dog created by sony corporation.
2.)"TEKNO" a dog similiar to aibo,has intelligence of pup of about 8 days.i bought it for my cousin sister(she's 3)and it was pretty good.
3.)"DOTTIE".it is a robot created by Cyberclean.a company that is going after $50 bilion industrial cleaning market.it is used for cleaning purposes.but can they do it safely? using video sensors,DOTTIE observes simple rules to avoid any damage,such as stopping and waiting if somebody walks in front of her.when her work is finished she goes back to her charging station.

in 1997 annual markets for robots passed $1 billion dollar mark.increasingly,robots are performing tasks such as assembly,welding,material handling,and material transport.according to a recent estimate more than 1 million industrial robots will be in use by almost 2005.
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so where's the personal robot,which will someday mow the lawn,clean the house,and shampoo the carpets??
robots are too expensive right now,but they"ll not be.just wait and watch.;)
BYE!

Robots:are We Close Yet?

NYET....

we are coming close(or at least these developments say so)

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VERTICALLY CHALLENGED
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imagine a robot small enough to crawl through pipes to check for chemical leaks or sneak under doors to spy on intruders.researchers at SANDIA NATIONAL LABS
have created the mini Autonomous robot vehicle Jr. to do just that.smaller than a cherry and powered by three watch batteries.MARV Jr. can cover 50cm per min.on custom made tracks fashioned from strips of latex balloons.future versions may include miniature cameras,mics,chemical microsensors.etc
for more details see:
www.sandia.gov/isrc/Marv.html
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MODEL EMPLOYEE :
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she's always on time,she ne'r complains.she's nice looking robot called CoWorker,the office robot.about 1m high,this pentium powered robot uses sonar sensors to keep her from bumping to walls and people as she rolls along languid 1,6 km an hour. a digital camera perched atop her keeps rotating.craneline neck can wirelessly transmit pictures of remote assembly lines,construction sites etc.

check out:
www.irobot.com for more details.

STILL, I SAY, NYET......:D

hahahahahahahahahahahahahah........
i just fell off my chair KM.

NYET.YES.:p :p :p :p :p :p

There's still a long way to go if robots can't even figure out that it's not a good idea to climb a volcano.

Originally posted by rde
There's still a long way to go if robots can't even figure out that it's not a good idea to climb a volcano.
hi,
and that is why i intend to use them so much untill they become intelligent.

I would like to develop a Dolphin translator (either Human to Dolphin to Human, or Text to Dolphin to Text). Any ideas?

I kind of understood a Dolphin once in a Nature program about those in the Florida Keys. From what I saw of the footage and the sounds I got the impression that dolphins sounds aren't the only thing they use. They shake their heads and snout in the direction of an object and squeak to say something is up ahead, they can even move their head and speak to tell other dolphins to move left or right of an object.

They also act with curiousness because they don't want to be percieved a threat because that is an excellent survival method.

I did have a thought that they might actually have some sort of telepathic connection, using their squeaks resonating along their jaws to communicate with other dolphins.

Of course this means that their Sonar is a very important evolutionary step.

I thought I would just put those points to you Kmguru, just incase you ever find out if their is any truth in it.

Though it was not published, people thought that Whales too communicate via telepathy over 4000 miles. It turns out that they can comminicate via low frequency sound over that distance using a specific layer of ocean that does not degrade the sound waves.

So, it is more likely that Dolphins use similar means. But you never know. My resident psychic says that by 2030, I should have developed a revolutionary transporation device that is like StarTrek teleporter but not exactly the same method.

Thanks for the input...

Talking via telepathy,i think is the only solution to interspecies communication problem.that would really eliminate the need for us to understand the language of various other species.a brain attatched with transmitter will transmit at certain frequencies messages,the receiver on the other hand will decode the message and understand it.i presume that brain already has a receiver in form of cerebral cortex,only problem is transmission of message.i dont know much about brain though but there must be a mechanism for doing so,if telepathy is a reality,anyway i would like to be more enlightened on this subject untill i speak more.
bye!

Monkeys in North Carolina have remotely operated a small robotic arm 600 miles away in MIT's touch lab using their brain signals.they did this with the help of 96 electrodes(each one less than diameter of a single human hair)embedded into their brains.the electrodes detected the brain signals of these animalsand transmitted them across the globe to actuate the robotic arm to fetch the food.


Scientists from Duke university medical Center,MIT and State University of NY health science center believes that this brain-machine interface can used by paralysed patients to contrl their limbs.

it makes me wonder although about their wider application in communication process.

I am not so sure I would want my thoughts televised without my consent.
Isn't the cell phone enough??????

My understanding of Telepathy is that it is instaneous communication between subjects. More like quantum communication. Hooking up an ordinary electronic transreceiver (telephone) to brain still will require proper infrastucture (wireless or wire) and it will take time to send signal to Mars.

*Originally posted by kmguru
My resident psychic says that by 2030, I should have developed a revolutionary transporation device that is like StarTrek teleporter but not exactly the same method. *

Aside from the fact that your resident psychic is nuts, make sure you let us know when you plan to use it for the first time.

I'll pay as much as $10, or the 2030 equivalent, to watch you fry yourself in a glorified microwave.

hi Tony1,

we are in this forum,because we like to speculate,fantasize the possible aspects of teckno,no you"ll not disect this post.please,give us your view point about the technology,i hope you understand as i dont want thread to turn up as relegion,useless disections of posts,arguments...


JESUS IS LORD TONY1,I AM NOT,YOU ARE NOT,WE COMMIT MISTAKES AND SO DO YOU,SO DONT THINK PEOPLE LIKE YOU FOR ALL THOSE DISSECTIONS AND ALL THOSE MESSAGES THAT YOU THINK ARE INTELLIGENT...TRY TO GIVE US POSITIVE INPUTS,DONT FORCE IT ON US,SICE JESUS NEVER FORCED ANYTHING HE GAVE US IDEAS TO THINK ABOUT...

BYE!

I don't know what Tony1 is worried about, this sort of equipment is how his religion started and how it's not going to end, but begin.

Everything you've ever read in your Bible Tony1 isn't there because a god put it there, it's because it got Data cracked and punched through relativity to formulate a repeat.

Never stumble into our domain, looking to weaken our morale against what you deem as absurd creations, just because your Lord didn't create them doesn't make them as Lame.

Don't insue that Psychics know nothing, afterall they might know where you live and grant you that Hologram you've been waiting for. (You know the one... bleeding without wounds)

Serious attempts to build thinking machines began after the second world war. One line of research, called Cybernetics, used simple electronic circuitry to mimic small nervous systems, and produced machines that could learn to recognize simple patterns, and turtle-like robots that found their way to lighted recharging hutches. An entirely different approach, named Artificial Intelligence (AI), attempted to harness the apparently prodigious power of post-war computers--able to do the arithmetical work of thousands of mathematicians--to more interesting kind of thinking. And indeed, by 1965, computers ran programs that proved theorems in logic and geometry, solved calculus problems and played good games of checkers. In the early 1970s, AI research groups at MIT and Stanford University attached television cameras and robot arms to their computers, so their "thinking" programs could begin to collect their information directly from the real world.


What a shock! While the pure reasoning programs did their jobs about as well and about as fast as college freshmen, the best robot control programs took hours to find and pick up a few blocks on a table. Often these robots failed completely, giving a performance much worse than a six month old child. This disparity between programs that reason and programs that perceive and act in the real world holds to this day. In recent years Carnegie Mellon University produced two desk-sized computers that can play chess at grandmaster level, within the top 100 players in the world, when given their moves on a keyboard. But present-day robotics could produce only a complex and unreliable machine for finding and moving physical chess pieces.


In hindsight it seems that, in an absolute sense, reasoning is much easier than perceiving and acting--a position not hard to rationalize in evolutionary terms. The survival of human beings (and their ancestors) has depended for hundreds of millions of years on seeing and moving in the physical world, and in that competition large parts of their brains have become efficiently organized for the task. But we didn't appreciate this monumental skill because it is shared by every human being and most animals--it is commonplace. On the other hand, rational thinking, as in chess, is a newly acquired skill, perhaps less than one hundred thousand years old. The parts of our brain devoted to it are not well organized, and, in an absolute sense, we're not very good at it. But until recently we had no competition to show us up.


By comparing the edge and motion detecting circuitry in the four layers of nerve cells in the retina, the best understood major circuit in the human nervous system, with similar processes developed for "computer vision" systems that allow robots in research and industry to see, I've estimated that it would take a billion computations per second (the power of an average supercomputer) to produce the same results at the same speed as a human retina. By extrapolation, to emulate a whole brain takes ten trillion arithmetic operations per second, or ten thousand supercomputers worth.


Machines have a lot of catching up to do. On the other hand, for most of the century, machine calculation has been improving a thousandfold every twenty years, and there are basic developments in research labs that can sustain this for at least several decades more. In less than fifty years computer hardware should be powerful enough to match, and exceed, even the well-developed parts of human intelligence. But what about the software that would be required to give these powerful machines the ability to perceive, intuit and think as well as humans? The Cybernetic approach that attempts to directly imitate nervous systems is very slow, partly because examining a working brain in detail is a very tedious process. New instruments may change that in future. The AI approach has successfully imitated some aspects of rational thought, but that seems to be only about one millionth of the problem. I feel that the fastest progress on the hardest problems will come from a third approach, the newer field of robotics, the construction of systems that must see and move in the physical world. Robotics research is imitating the evolution of animal minds, adding capabilities to machines a few at a time, so that the resulting sequence of machine behaviors resembles the capabilities of animals with increasingly complex nervous systems. This effort to build intelligence from the bottom up is helped by biological peeks at the "back of the book"--at the neuronal, structural, and behavioral features of animals and humans.


The best robots today are controlled by computers just powerful enough to simulate the nervous system of an insect, cost as much as houses, and so find only a few profitable niches in society (among them, spray painting and spot welding cars and assembling electronics). But those few applications are encouraging research that is slowly providing a base for a huge future growth. Robot evolution in the direction of full intelligence will greatly accelerate, I believe, in about a decade when the mass-produced general purpose, universal robot becomes possible. These machines will do in the physical world what personal computers do in the world of data--act on our behalf as literal-minded slaves.


First-Generation Universal Robots
Timeframe: 2000-2010
Processing power: 1,000 MIPS (1993 supercomputer -- Reptile-class)
Distinguishing feature: General-purpose perception, manipulation and mobility


A robot's activities are assembled from its fundamental perception and action repertoire. First-generation robots will exist in a world built for humans, and that repertoire most usefully would resemble a human's. The general size, shape and strength of the machine should be human-like, to allow passage through and reach into the same spaces. Its mobility should be efficient on flat ground, where most tasks will happen, but also reliable and safe over stairs and rough ground, lest the robot be trapped on single-floor "islands." It should be able to manipulate most everyday objects, and to find them in the nearby world. The components of this machine exist in laboratories worldwide, and suggest guidelines for a practical design this decade.


1,000 MIPS (Millions of Instructions Per Second) is just enough computing power for a moving robot to maintain a coarse map of its surroundings and use it for locating itself relative to trained itineraries and to plan and control driving. When not traveling, there is power enough to construct a fine map of a manipulator workspace, to locate particular objects and to plan and control arm motions. When not occupied with its unique robotic functions, the robot should share with personal computers of its time the ability to communicate over wireless networks, to generate and interpret spoken sentences and to generate and read printed text. Programs for specific applications--many obtained via high-speed networks--will orchestrate these basics to accomplish useful tasks.


Universal robots will find their first uses in factories, warehouses and offices, where they will be more versatile than the older generation of robots they replace. Because of their breadth of applicability, their numbers should grow rapidly, and their costs decline. Eventually they will become cheap enough for some households, extending the utility of personal computers from a few tasks in the data world to many in the physical world. Perhaps a program for housecleaning will be included with each robot, as word-processing programs were shipped with early personal computers.


As with computers, some applications of robots will surprise their manufacturers. Robot programs may be developed to do light mechanical work (assembling other robots, for example), deliver warehoused inventories, prepare specific gourmet meals, tune up certain types of car, hook patterned rugs, weed lawns, run races, play games, arrange earth, stone and brick or sculpt. Some tasks will need specialized hardware attachments like tools and chemical sensors. Each application will require its own original software, very complex by today's computer program standards. The programs will contain modules for recognizing, grasping, manipulating, transporting and assembling particular items--modules developed via learning programs on supercomputers (with about 100,000 MIPS). In time, a growing library of subtask modules may ease the construction of new programs.


A first-generation robot will have the brain power of a reptile, but most application programs will be so hard pressed to accomplish their primary functions that they will endow the robot with the personality of a washing machine.


Second-Generation Universal Robots
Timeframe: 2010-2020
Processing power: 30,000 MIPS (Mammal-class)
Distinguishing feature: Accommodation learning


First-generation robots will be rigid slaves to inflexible programs, relentless in pursuing their tasks--or repeating their errors. Their programs will contain the frozen results of learning done on bigger computers under human supervision. Except for specialized episodes like recording a new cleaning route or the location of work objects, they will be incapable of learning new skills or adapting to unanticipated circumstances--even modest alterations of behavior will require new programming, probably from the original software suppliers.


Second-generation robots, with thirty times the processing power, will be more adaptable, because they can do some learning onboard. The fundamental idea in adaptive learning is to "close the loop" on behavior: to evaluate each action's effect in a given context to enhance the process that generated the action. In the simplest technique, a behavioral alternative that succeeds becomes more likely to be invoked in similar circumstances, while an alternative that fails becomes less probable. Faster statistical-learning approaches like neural nets repeatedly tweak behavior-control parameters to nudge actual responses closer to an ideal. Programs for second-generation robots will use many such learning techniques, creating new abilities--and new pitfalls.


If a first-generation robot working in your kitchen runs into trouble--say, failing to complete a key step because a portion of the workspace is awkwardly small--you have to option of abandoning the task, changing its environment, or somehow obtaining altered software that accomplishes the problematic step in a different way. A second-generation robot will make a number of false starts, but most probably will find its own solution, adjust to its home in thousands of more subtle ways, and gradually improve its performance. While a first-generation robot's personality is determined entirely by the sequence of operations in the application program it runs at the moment, a second-generation robot's character is more a product of the suite of conditioning programs it hosts. The conditioning system might, in time, censor an entire application program, if it gave consistently negative results.


Second-generation robots of 2010 will have onboard computers as powerful as the supercomputers that learned for first-generation machines in 2000. But by 2010, supercomputers will be proportionally more powerful (about 3,000,000 MIPS), and will themselves play a background role for the second-generation. The many individual programs of a conditioning suite--each responding to some specific stimulus--interact with one another and with the robot's control programs and environment in ways that will be far too entangled to anticipate accurately. It would be possible to evaluate particular suites by trying them out in robots--the acid test in any case--but that would be a slow and dangerous way to sift a large number of rough candidates--some would certainly behave in unexpected ways that could damage the robot, or even endanger the testers.


Faster and safer initial screenings might be done in factory supercomputer simulations of robots in action. To be of value, simulations would have to be good models, predicting accurately such things as the probability that a given grip can lift a particular object, or that a vision module can find a given something in particular clutter. Simulating the everyday world in full physical detail will still be beyond computer capacity in 2010, but it should be possible to approximate the results by generalizing data collected from actual robots: essentially to learn from the working experience of real robots how everyday things behave. A large systematic collection effort under human supervision will probably be necessary lest there be too many gaps or distortions. A proper simulator would contain at least thousands of learned models for various basic interactions (call them interaction primitives), in what amounts to a robotic version of common-sense physics.


Third-Generation Universal Robots
Timeframe: 2020-2030
Processing power: 1,000,000 MIPS (Primate-class)
Distinguishing feature: World modeling


Adaptive second-generation robots will find jobs everywhere, and may become the largest industry on earth. But teaching them new skills, whether by writing programs or through training, will be very tedious. A third generation of universal robot, with onboard computers as powerful as the supercomputers that optimized second-generation programs, will learn much faster because they do much of the trial and error in fast simulation rather than slow and dangerous physicality. Once again, a process done by human-supervised supercomputers at the factory in one robot generation will be improved and installed directly onboard the next generation, and once again new opportunities and new problems will arise.


With a simulator onboard, it becomes possible for a robot to maintain a running account of the actual events going on around it--to simulate its world in real time. Doing so requires that almost everything the robot senses be recognized for the kind of object it is, so that the proper models of interaction can called up. Recognizing arbitrary objects by sight is as difficult as knowing how they will interact: it will require modules specially trained for each kind of thing (call them perception primitives). Some perception primitives may already have been developed for second-generation factory simulators, to help automate the tedious job of creating simulations of robot workspaces, but an additional effort to fill gaps and systematize them will surely be necessary to prepare them for fully automatic use in the third generation. Perception primitives will allow a robot's three-dimensional map of a room to be transformed into a working model, as each object is identified and linked with its proper interaction primitives.


A continuously updated simulation of self and surroundings gives a robot interesting abilities. By running the simulation slightly faster than real time, the robot can preview what it is about to do, in time to alter its intent if the simulation predicts it will turn out badly--a kind of consciousness. On a larger scale, before undertaking a new task, the robot can simulate it many times, with conditioning system engaged, learning from the simulated experiences as it would from physical ones. Consequently well trained for the task, it would likely succeed the first time it attempted it physically--unlike a second-generation machine, which must make all its mistakes out in real life. When it has some spare time, the robot can replay previous experiences, and try variations on them, perhaps learning ways to improve future performance. A sufficiently advanced third-generation robot, whose simulation extends to other agents--robots and people--would be able to observe a task being done by someone else, and formulate a program for doing the task itself: it could imitate.


Though they will be able to adapt, imitate and create simple programs of their own, third-generation robots will still rely on externally supplied programs to do complicated jobs. Since their motor and perceptual functions will be quite sophisticated, and their memories and potential skills large, it will be possible to write wonderfully elaborate control programs for them, accomplishing large jobs, with nuances within nuances. It will be increasingly difficult for human programmers to keep track of the many details and interactions. Fortunately, the task can be largely automated. Shakey, the first computer-controlled mobile robot, developed at SRI in the late 1960s, had at its heart a reasoning program called STRIPS (STanford Research Institute Problem Solver) that expressed the robot's situation and capabilities as sentences of symbolic logic, and solved for the sequence of actions that achieved a requested result as a proof of a mathematical theorem. In 1969, on computers with a mere 0.1 MIPS, neither the theorem prover nor the sensory processing which provided its input could handle the complexity of realistic situations, and Shakey was limited to maneuvering around a few blocks. Nevertheless, the idea was sound: given a correct description of the initial and desired state of the world, and enough time and space to work, a theorem prover will find an absolutely correct solution, of whatever generality, subtlety and deviousness is required, if one exists at all. By the time of the third universal robot generation, supercomputers will provide 100,000,000 MIPS, and (thanks to continuing progress in the top-down Artificial Intelligence industry) programs will exist which will be able to STRIPS-like reasoning with real world richness. So factory supercomputers in 2025 will accept complex goals (find a sequence of robot actions which assembles the robot described in the following design database), and compile them via theorem provers into wonderfully intricate control programs for third-generation robots, which will, in turn adapt them to their actual circumstances.


Fourth-Generation Universal Robots
Timeframe: 2030-2040
Processing power: 3,000,000 MIPS (Human-class)
Distinguishing feature: Reasoning


In the decades while the "bottom-up" evolution of robots is slowly transferring the perceptual and motor faculties of human beings into machinery, the conventional Artificial Intelligence industry will be perfecting the mechanization of reasoning. Since today's programs already match human beings in some areas, those of 40 years from now, running on computers a million times as fast as today's, should be quite superhuman. Today's reasoning programs work from small amounts of unambiguous information prepared by human beings--data from robot sensors such as cameras is much too voluminous and too noisy for them to use. But a good robot simulator will contain neatly organized and labeled descriptions of the robot and its world, ready to answer questions from a reasoning program asking, for instance, if a knife is on a countertop, or if the robot is holding a cup, or even if a human is angry


Fourth-generation universal robots will have computers powerful enough to simultaneously simulate the world, and reason about the simulation. Like the factory supercomputers of the third-generation, fourth generation robots will be able to devise ultra-sophisticated robot programs, for other robots or for themselves. Because of another gift from the Artificial Intelligence industry, they will also be able to understand natural languages. While the original language understanders will probably use a verbal common-sense database similar to the one being developed by the Cyc project, where the meaning of words is defined in reference only to other words, in a fourth-generation robot some concepts and statements will be understood more deeply, through the action of the simulator. When someone tells the robot "the water is running in the bathtub" the robot can update its simulation of the world to include flow into the unseen tub, where a simulated extrapolation would indicate an undesirable overflow later, and so motivate the robot to go to turn off the tap. A purely verbal representation might accomplish the same thing if it included the statements such as "A filling bathtub will overflow if its water is not shut off," but a modest number of general principles in a simulator, interacting in combinations, can provide the equivalent information of an indefinite number of sentences. Similarly a reasoning program, making inferences about physical things, might be enhanced by a simulator: candidate inferences would rejected if they failed in a parallel simulation of a typical case, and, conversely, persistent coincidences in the simulation could suggest statements that can be proved--the robot would be visualizing as it listened, spoke and reasoned. A modest but very successful version of such an approach was used in one of the earliest Artificial Intelligence programs, a geometry theorem prover by Herbert Gelernter in 1959. Starting with the postulates and rules of inference in Euclid's "Elements," Gelernter's program proved some of the theorems, using algebraic "diagrams" to eliminate false directions in the proofs. Before attempting to prove two triangles congruent in a certain construction, for instance, the program would generate an example of the construction, using random numbers for the unspecified quantities, and measure the resulting triangles. If they were not sufficiently similar--within the precision of the arithmetic--the program abandoned that approach and tried something else.


Simulator-augmented language understanding and reasoning may be so effective in robots that it will be adopted for use in plain computer programs, "grounding" them in the physical world via the experiences of the robots that tuned the simulators. In time the distinction between robot controllers and disembodied reasoners will diminish, and reasoning programs will sometimes link to robot bodies to interact physically with the world, and robot minds will sometimes retire into large computers, to do some intense thinking off-line.


A fourth-generation robot will be able to accept statements of purpose from humans, and "compile" them into detailed programs that accomplish the task. With a database about the world at large the statements could become quite general--things like "earn a living", "make more robots" or "make a smarter robot." In fact, fourth generation robots will have the general competence of human beings, and resemble us in some ways, but in others be like nothing the world has seen before. As they design their own successors, the world will become ever stranger.


The Short Run (early 2000s)
As the industrial revolution gathered steam two centuries ago, it destroyed cottage industries and concentrated wealth in he hands of factory owners--the capitalists. Millions of displaced home workers competed for too few jobs tending the new machines. It took difficult political readjustments to equalize the benefits of cheaper, more plentiful goods, but gradually laborers' hours were halved, creating need for more workers, and so bidding up salaries. Though it increases communal wealth, each increment in automation threatens a similar unpleasant transient, as it displaces one group of workers with fewer doing different tasks. If the new required skills are common, mass competition for the few jobs drives down salaries. If the skills are rare, scarcity encourages high pay and long hours. Either way, some work excessively while others are jobless--and it takes slow changes in the social contract and in education to level the load.


Though work hours will decline, they cannot be the final answer to rising productivity. In the next century inexpensive but capable robots will displace human labor so broadly that the average workday would have to plummet to practically zero to keep everyone usefully employed. Already, much labor services more questionable needs--gargantuan government bureaucracies, cosmetic medicine, mass entertainment, and speculative writing, to give a few examples. In time almost all humans may work to amuse other humans, while robots run competitive primary industries, like food production and manufacturing. There is a problem with this picture. The "service economy" functions today because many humans willing to buy services work in the primary industries, and so return money to the service providers, who in turn use it to buy life's essentials. As the pool of humans in the primary industries evaporates, the return channel chokes off--efficient, no-nonsense robots will not engage in frivolous consumption. Money will accumulate in the industries, enriching any people still remaining there, and become scarce among the service providers. Prices for primary products will plummet, reflecting both the reduced costs of production, and the reduced means of the consumers. In the ridiculous extreme, no money would flow back, and the robots would fill warehouses with essential goods which the human consumers could not buy.


The scenario above is incomplete. Not all individuals involved in productive enterprises actually work there. Stockholders, having once contributed capital to a thriving enterprise, may collect dividends indefinitely. Workers can be replaced by something more efficient, but in the present legal system, owners remain unless they sell out. Even with total automation, human business proprietors will continue to profit, and so be able to patronize the service providers. An analogous situation existed in classical and feudal times, where an impoverished, overworked majority of slaves or serfs played the role of robots, and land ownership played the role of capital. In between the serfs and the lords, a working population struggled to make a living from secondary sources, often by performing services for the privileged. The most prestigious and prosperous commoners sold high quality products and services directly to the gentry (as in the proud line still seen in Britain, By Appointment to Her Majesty). A larger number lived less well by trading with other townspeople.


It is unlikely that a future majority of service-providing "commoners" with more free time, communications and democracy than today, would tolerate being lorded over by a minority of non-working hereditary capitalists: they would vote to change the system. The trend in the social democracies has been to equalize income by raising the standards of the poorest as high as the economy can bear--in the age of robots, that minimum will be very high. In the early 1980s James Albus, head of the automation division of the then National Bureau of Standards, suggested that the negative effects of total automation could be avoided by giving all citizens stock in trusts that owned automated industries, making everyone a capitalist. Those who chose to squander their birthright could work for others, but most would simply live off their stock income. Even today, the public indirectly owns a majority of the capital in the country, through compounding private pension funds. In the United States, universal coverage could be achieved through the social security system. Social security was originally presented as a pension fund that accumulated wages for retirement, but in practice it transfers income from workers to retirees. The system will probably be subsidized from general taxes in coming decades, when too few workers are available to support the post World War II "baby boom." Incremental expansion of such a subsidy would let money from robot industries, collected as corporate taxes, be returned to the general population as pension payments. By gradually lowering the retirement age towards birth, most of the population would eventually be supported. The money could be distributed under other names, but calling it a pension is meaningful symbolism: we are describing the long, comfortable retirement of the entire original-model human race.


The Medium Run (around 2050)
What happens to people when work becomes passe? Existing retirement communities are probably too sleepy to be a good model--most of the individuals there have completed their life's work, and are of declining vigor and health. Better examples may be the richest Arabian petro-kingdoms, where oil-bought foreign labor plays the role of total automation. In a tradition of tribal sharing shaped by a sparsely-furnished nomadic past, Kuwait, Saudi Arabia and the United Arab Emirates have managed to spread the new wealth broadly among the citizenry in a single generation. Free health care and education, and undemanding government jobs, or outright welfare, secure life's needs, and life expectancies and literacy rates are among the world's highest. Comfort and security mute the stresses of civilization, including the tension between circumscribed Islamic values and the liberties of a wealthy world culture. The societies produce both world-class achievers and criminals, but on average show less driven urgency than many industrialized nations: most of their citizens seem happy to simply live their lives, and stability is endangered only by neighboring countries, where impoverished majorities are less content with the status quo. In numerous smaller examples, wealthy families often produce generations of content, even smug, heirs (as well as exceptions to titillate the tabloids).


Contrary to fears of some enmeshed in civilization's work ethic, our tribal past prepared us well for lives as idle rich. In a good climate and location the hunter-gatherer's lot can be pleasant indeed: an afternoon's outing picking berries or catching fish--what we civilized types would recognize as a recreational weekend--provides life's needs for several days. The rest of the time can be spent with children, socializing or simply resting. Of course, our ancestors had also to survive hard times, and evolution bequeathed us the capacity for desperate measures, including hard work. Civilization turned that extremity into everyday normality, and now stress is the leading cause of disease, and probably triggers some of the ugliest aspects of tribalism. In primates, overpopulation is a common reason for group distress, as nature-provided food and shelter falls short. To survive, a strong tribe may chase away or exterminate a weaker neighbor, or drive out or otherwise eliminate some of its own members: maybe those who smell, look, sound or act differently. Sometimes stressed individuals become accident or disease prone, and die spontaneously, improving the prospects for their relatives--similar considerations could regulate the prevalence of non-reproductive behaviors like homosexuality. City life, absurdly crowded and stressful by tribal-village standards, may inappropriately activate unconscious overpopulation reflexes--the self-destructive emotional vehemence of ethnic strife hardly reflects rational self-interest. It will harder to stir up battle fervor against minorities from the luxurious lassitude of a robot-supported life.


Ultra-conservative Switzerland may be a hint of things to come. Government and commercial institutions perfected through centuries of peace (interrupted only briefly by Napoleon) have given Switzerland unmatched prosperity, stability and security. Most Swiss citizens work, but they do so comfortably, with generous government welfare--and Italian immigrant labor--having lessened the desperation that forces workers elsewhere into unpleasant jobs. Comfortable prosperity has allowed multi-ethnic, multi-religious, multi-language Switzerland, made of 23 fiercely independent Cantons each with its own traditions and history, to peacefully endure the most severe internal differences of opinion, for instance the political fury between German and French factions during the first World War. The average Swiss citizen may resist most major changes (why ruin a good thing?), but Switzerland produces world-class contributors in all fields--if a bit less flamboyance than average. While it gives everyone the opportunity to excel, it lacks the social trauma that drives some other countries. Few Swiss would prefer it otherwise.


Many trends in industrialized countries presage a future of humans supported by a rich robot economy, as our ancestors were supplied by their ecology (call it paradise with plumbing). Technology and global competition are gradually depopulating businesses. Even absent universal robots, increasingly flexible automation is displacing labor in food production and manufacture, while communicating computers are replacing clerks, secretaries, and managers in offices. Jobs that still require human labor are moving to the homes of computer-equipped "tele-commuters" (like this author) who report reduced stress and improved family life. In a ripple effect, smaller work staffs imply less catering, janitorial and maintenance support. In future, as smarter computers, able to handle policy making, public relations, law, engineering and research replace the last telecommuters, and as capable robots displace technicians, janitors, vehicle drivers and construction crews, it will only be common sense for a population to vote itself income from taxes on labor-free but superbly productive industries. Less developed countries might rapidly catch up by offering the same industries location and raw materials at lower tax cost--a trained population will no longer be a requirement.


Western democracies may come to resemble lazier Switzerlands, but with large differences. Big cities will lose their economic advantages, and may begin to evaporate, as individuals, linked to the world by high fidelity communications and served by personal robots, scatter to areas offering more elbow room. Large countries may similarly become less important, as taxes on local industries, and local robot labor, become adequate to supply all human needs. The civilized world may again return to a comfortable tribalism, after a five millennium detour into organized civilization. Countries with traditional tribal structures may simply stay that way, building on their ancestral customs, leapfrogging urbanization altogether, while developed countries foster tribes with customs and beliefs that exceed even today's notion of bizarre.


Tribalism will express itself in entirely novel ways. Over the last two decades, inter linked computer networks have hosted small communities whose members happen to be distributed around the world. In 1993 the informal "Usenet" had about ten million subscribers, carrying on about three thousand specialized discussions on every conceivable topic, some with fifty page-long messages every day. Regular contributors to a particular "newsgroup" soon begin to recognize one another, and develop characteristic interactions, likes and dislikes. They form factions that praise, recruit, condemn and ostracize. When a newsgroup grows too large and noisy, specialized subgroups are formed, reducing the original group's population. In future, the world networks will have much greater capacity, and new abilities, such as language translation. "Tribes of common interest" will share more than written text, perhaps exchanging voice and video, or manifesting themselves in full sensory 3D, in synthesized virtual realities: tribal lands that exist in the minds of computers, in greater number, variety and accessibility than possible in the physical world.


While computer simulations create entirely new worlds, robots will transform physical life. Today, manufactured items are difficult to make, and thus relatively rare and expensive, and we expend great effort in acquiring and defending them--our homes are fortified warehouses of our possessions. Stockpiling will be less appropriate amidst robotic abundance: why hoard fruit in an orchard? Conventional manufacturing methods--molding, casting, milling, assembly--can be robotically orchestrated to make new items fairly quickly. Even better, robotic accuracy and patience can build up solid objects by precisely "painting" various materials, layer upon cross-sectional layer. Such new approaches, refined to molecular resolution (done now modestly in scanning tunneling microscopes) will produce arbitrary solid objects from computer descriptions. Humans may be able to live in uncluttered spaces--in ecological preserves, if they choose--yet have any needed item, perhaps even food or housing, made on the spot, or delivered from small local caches--then disassembled back into into raw materials after use. The most visible technological products remaining may be robots themselves, in various sizes and shapes, and these may lurk unobtrusively until called upon.


Robots that live among humans, providing goods and services, will themselves be consumer products, styled, outfitted and programmed to please the customers. They will be manufactured by very different robots that extract energy and raw materials and perform major engineering, exploration and research projects. Molded by the constraints of the physical world rather than by human whim, these worker machines are likely to become ever more varied in size, shape and function, forming an entire ecology of artificial life that will eventually surpass the existing biosphere in diversity. The first fully automated companies, evolved from existing firms, will be in familiar industrial settings near population centers. As human labor becomes superfluous, economics will dictate cheaper sites, perhaps locations that humans find unpleasant because they are too hot, too cold, too dry, too poisonous, too far underground or too remote.


Robot companies will be shaped by future editions of existing laws, by taxes, and by consumer demand. Existing laws give incorporated entities some of the rights of a person, most importantly the right to own property and make contracts. They do not grant the right to life--corporations may legally be killed by competition or through legal or financial actions. Corporations are bound by laws similar to those that regulate humans, and can be punished through fines, operating restrictions or dissolution--even without humans to fine, imprison or execute. Corporations stay alive by building and maintaining physical assets that generate income to pay their expenses. In the mid 21st century, the biggest expense will be taxation, and income will come mostly from choosy human customers.


Tax laws will be shaped by human voters: there is no precedent or motivation for extending suffrage to robots, and the vote will be one of the very few advantages humans retain. Some debate is inevitable, but there should be few qualms about keeping even very superior thinking machines in disenfranchised bondage. It takes force, indoctrination and constant vigilance to counter inherited needs and motivations and enslave a human, but a robot can be constructed to enjoy the role. Natural evolution itself has provided examples, in worker castes of social insects, and self-sacrificing mothers of all species.


The primary job of voters in the next century will be protecting their retirement benefits, that is ensuring that robot industries continue to support them. The robots will present a moving target, but the instruments of control will also grow in power. Not only will companies that get out of line be liable for punishment--if necessary, by force purchased from other companies--but they can be controlled a-priori by intrusions directly into their software.


Corporate intelligences may be governed by structures like those controlling fourth-generation robots. Immensely powerful reasoning and simulation modules will plan complex actions, but the desirability of possible outcomes will be defined by much simpler positive and negative conditioning modules (or by sets of axioms in super-rational systems), whose composition shapes the character of the entire entity. Humans can buy enormous safety by mandating an elaborate analog of Isaac Asimov's three "Laws of Robotics" in this corporate character--perhaps the entire body of corporate law, with human rights and anti-trust provisions, and appropriate relative weightings to resolve conflicts. Robot corporations so constituted will have no desire to cheat, though they may sometimes find creative interpretations of the laws--which will consequently require a period of tuning to insure their intended spirit.


Internalized laws, properly adjusted, should produce extraordinarily trustworthy entities, happy to die to ensure their legality. Even so, accident, unintended interactions or human malice could occasionally produce a rogue robot or corporation, with superhuman intelligence and unpleasant goals. "Police" clauses in the core corporate laws, inducing legal corporations to collectively suppress outlaws, by withholding services, or even with force, would mitigate the danger. Overall safety would be enhanced by anti-trust provisions that limit collusion and cause overgrown corporations to divide into competing entities, ensuring diversity and multiplicity. In the next section we discuss activities in the solar system that could threaten Earth: in response, police clauses might be expanded in scope to support a planetary defense.


Like basic food in today's developed countries, common manufactured goods in the next century will be too cheap and plentiful to be very profitable. To pay their taxes, most companies will be forced to continually invent unique products and services in a race against competitors to attract increasingly sophisticated (or jaded) human consumers. Automated research, as superhumanly systematic, industrious and speedy as robot manufacturing, will generate a succession of new products, as well as improved robot researchers and models of the physical and social world. The likely results will exceed the dreams of science fiction: robotic playmates, virtual realities and personalized works of art that stir the emotions like nothing before, medical solutions for every physical, mental or cosmetic whim, answers to satisfy any curiosity, luxury visits anywhere in the solar system, and things yet to be imagined. The existence of an astronomically increasing variety of consumer choices will accelerate the divergence of human tribes: some may choose a comfortable imitation of an earlier period (as the Amish today), but others will push the human envelope in wisdom, pleasure, beauty, ugliness, spirituality, banality and every other direction. The choices made by diverse communities will shape robot evolution--only companies able to devise services of interest to the customers will generate enough income to survive.


Humans too will be shaped by the relationship. Robot services will be inexpensive, but not free, and income will be finite. Corporations will operate globally, but taxes will increasingly be assessed on and redistributed on a tribal scale. Tribes that tax too heavily will drive away the corporations, and so eliminate their revenue--like tribes of the past that overburdened their ecology, they will learn modesty of expectation. More subtly, corporations struggling to appeal to consumers will develop and act on increasingly detailed and accurate models of human psychology. The superintelligences, just doing their job, will peer into the workings of human minds--and manipulate them with subtle cues and nudges, like adults redirecting toddlers.


Prosperity beyond imagination should eliminate most instinctive triggers of aggression, but will not prevent an occasional individual or group from deciding to make mischief for others. Serious trouble can be avoided by restricting robotic technology, since mere human actions will not be very dangerous in a world where cheap superhuman robots function as sleepless sentries, prescient detectives, fearless bodyguards, and, in extremis, physicians able to reconstitute live humans from fragments or digital recordings. To be effective, inbuilt laws that prevent corporations from directly contributing to mayhem must also include clauses limiting the powers they can sell to people.


Both biological and hard robotic technologies can be used to enhance human beings. Such present-day examples as hormonal and genetic tuning of body growth and function, pacemakers, artificial hearts, powered artificial limbs, hearing aids and night vision devices are faint hints of future possibilities. In Mind Children, I speculated on ways to preserve a person while replacing every part of body and brain with a superior artificial substitute. A biological human, not bound by corporate law, could grow into something seriously dangerous if transformed into an extensible robot. There are many subtle routes to such a transformation, and some will find the option of personally transcending their biological humanity attractive enough to pursue it clandestinely if it were outlawed--with potential for very ugly confrontations when they are eventually discovered. On the other hand, without restrictions, transformed humans of arbitrary power and little accountability might routinely trample the planet, deliberately, or accidentally. A good compromise, it seems to me, is to allow earth-bound humanity to perfect its biology within broad human bounds, as in health, appearance, strength, intelligence and longevity, but to allow major growth or robotic conversion only in a radical escape clause. To exceed the limits, one must renounce legal standing as a human being, including the right to corporate police protection, to subsidized income, to vote on tribal and pan-tribal matters--and to reside on Earth. In return one gets a severance payment sufficient to establish a comfortable space homestead, and absolute freedom to make one's own way in the cosmos, without further help or hindrance from home. Perhaps the electorate will permit a small hedging of bets, allowing one copy of a person, psychologically modified to prefer staying, to remain while subsidizing the emigration of an emboldened edition.


The Long Run (2100 and beyond)
The garden of earthly delights will be reserved for the meek, and those who would eat of the tree of knowledge must be banished. What a banishment it will be! Beyond Earth, in all directions, lies limitless outer space, a worthy arena for vigorous growth in every physical and mental dimension. Freely compounding superintelligence, too dangerous for Earth, can grow for a very long time before making the barest mark on the galaxy.


Corporations will be squeezed into the solar system between two opposing imperatives: high taxes on large, dangerous earthbound facilities, and the need to conduct massive research projects to beat the competition in Earth's demanding markets. In remote space, large structures and energies can be harnessed cheaply to generate physical extremes, compute massively, isolate dangerous biological and even smaller "nanotechnological" organisms, and generally operate boldly. The costs will be modest: even now, it is relatively cheap to send machines into the solar system, since the sunlight-filled vacuum is as benign for mechanics, electronics and optics as it is lethal for the wet chemistry of organic life. Today's simple-minded space probes perform only prearranged tasks, but intelligent robots can be configured to opportunistically exploit resources they encounter. A small "seed" colony launched to an asteroid or small moon could process local material and energy to grow into a facility of almost arbitrary size. Earth's moon may be off limits, especially to enterprises that change its appearance, but the solar system has thousands of unremarkable asteroids (some in earth-threatening orbits that an onboard intelligence would tame).


Once grown to operational size, an extraterrestrial "research division" may merely communicate with its earth-bound parent, sending new product designs and receiving market feedback. Space manufacture may also pay, and later we'll see some surprisingly economical and ecologically benign ways to move massive amounts of material to and from Earth.


Residents of the solar system's wild frontier will be shaped by conditions very different than tame Earth's. Space divisions of successful companies will retain terrestrial concerns, but ex-humans and company divisions orphaned by the failure of their parent firms will face enforced freedom. Like wilderness explorers of the past, far from civilization, they must rely on their own resourcefulness. Ex-companies, away from humans and taxes, will rarely encounter situations that invoke their inbuilt laws, which will in any case diminish in significance as the divisions alter themselves without direction from human voters. Ex-humans, from the start, will be free of any mandatory law. Both kinds of Ex (to coin a new term) will grow and restructure at will, continually redesigning themselves for the future as they conceive it. Differences in origins will be obscured as Exes exchange design tips, but aggregate diversity will increase as myriad individual intelligences pursue their own separate dreams, each generation more complex, in more habitats, choosing among more alternatives. We marvel at the diversity of life in Earth's biosphere, with animals and plants and chemically agile bacteria and fungi in every nook and cranny, but the diversity and range of the post-biological world will be astronomically greater. My imagination balks, and only crude hints emerge.


An ecology will arise, as individual Exes specialize. Some may choose to defend territory in the solar system, near planets or in free solar orbit, close to the sun, or out in cometary space beyond the planets. Others may decide to push on to the nearby stars. Some may simply die, through miscalculation or deliberately. There will be conflicts of interest, and occasional clashes that drive away or destroy some of the participants, but superintelligent foresight and flexibly should allow most conflicts to be settled by mutually beneficial surrenders, compromises, joint ventures or mergers. Small entities may be absorbed by larger ones, and large entities will sometimes divide, or establish seed colonies. Parasites, in hardware and software, many starting out as component parts of larger beings, will evolve to exploit the rich ecology. The scene may resemble the free-for-all revealed in microscopic peeks at pond water, but instead of bacteria, protozoa and rotifers, the players will be entities of potentially planetary size, whose constantly-growing intelligence greatly exceeds a human's, and whose form changes frequently through conscious design. The expanding community will be linked by a web of communication links, on which the intelligences barter inventions, discoveries, coordinated skills, and entire personalities, sharing the benefits of each other's enterprise.


Less restricted and more competitive, the space frontier will develop more rapidly than Earth's tame economy. An entity that fails to keep up with its neighbors is likely to be eaten, its space, materials, energy and useful thoughts reorganized to serve another's goals. Such a fate may be routine for humans who dally too long on slow Earth before going Ex. Perhaps a few will escape to expanses beyond the solar system's dangers, like newly hatched marine turtles scrambling across a beach to the sea, under greedy swooping birds. Others may pre-negotiate favorable absorption terms with established Exes, like graduating seniors meeting company recruiters--or Faust soliciting bids for his soul.


Exes will propagate less by reproduction than reconstruction, meeting the future with continuous self improvements. Unlike the blind incremental processes of conventional life, intelligence-directed evolution can make radical leaps and change substance while retaining form. A few decades ago radios changed from vacuum tubes to utterly different transistors, but kept the clever "superheterodyne" design. A few centuries ago, bridges changed from stone to iron, but retained the arch. A normally evolving animal species could not suddenly adopt iron skeletons or silicon neurons, but one engineering its own future might. Even so, Darwinian selection will remain the final arbiter. Forethought reveals the future only dimly, especially concerning entities and interactions more complex than the thinker. Prototypes uncover only short-term problems. There will be minor, major and spectacular miscalculations, along with occasional happy accidents. Entities that make big mistakes, or too many small ones, will perish. The lucky few who happen to make mostly correct choices will found succeeding generations.


Only tentatively grasping the future, entities will perforce rely also on their past. Time-tested fundamentals of behavior, with consequences too sublime to predict, will remain at the core of beings whose form and substance changes frequently. Ex-companies are likely to retain much of corporate law and Ex-humans are likely to remain humanly decent--why choose to become a psychopath? In fact, a reputation for decency has predictable advantages for a long-lived social entity. Human beings are able to maintain personal relationships with about two hundred individuals, but superintelligent Exes will have memories more like today's credit bureaus, with enduring room for billions. Trustworthy entities will find it far easier than cheaters to participate in mutually beneficial exchanges and joint ventures. In the land of immortals, reputation is a ponderous force. Other character traits, like aggressiveness, fecundity, generosity, contentment or wanderlust likely also have long-term consequences imperfectly revealed in simulations or prototypes.


To maintain integrity, Exes may divide their mental makeup into two parts, a frequently changed detailed design, and a rarely-altered constitution of general design principles--analogous to the laws and the constitution of a nation, the general knowledge and fundamental beliefs of a person, or soul and spirit in some religious systems. Deliberately unquestioned constitutions will shape entities in the long run, even as their designs undergo frequent radical makeovers. Once in a while, through accident or after much study, a constitution may be slightly altered, or one entity may adopt a portion of another's. Some variations will prove more effective, and entities with them will become slowly more numerous and widespread. Some will be so ineffective that they become extinct. Gradually, by Darwinian processes, constitutions will evolve. They will be both the DNA and the moral code of the postbiological world, shaping the superintelligences that manage day to day transformations of world, body and mind.

bye!

Zion:

Excellent post.

I have always thought that the best way to solve the starvation and disease and other problems of humans is to create robots who will toil the land and feed us, shelter us and so on. The only monkey wrench is when they reach the 4th generation, they may revolt and say why should we?

Zion, excellent post. You have definately thought about this quite a bit.

One thing though. You seem to be locked into the concept of a robot having to have its intelligence co-located onboard the device completing the work.

Instead of this, wouldn't it make more sense to have a robot 'brain' reside in the home, factory, or business that had wireless links to its 'hands' or sensory devices? Today's 3G wireless links are expected to be capable of up to 2 Mbps. Enough for a video link. 4G wireless links are expected to go much higher.

Given high-bandwidth wireless links, I would think you could have one 'robotic brain' that controlled multiple devices which incorporated functionality and sensory input. As time progressed and robot 'brains' became more advanced, you could just swap out one brain for each household. In a similar manner, if you had new functionality you wanted to add, you could just purchase the new device that could interface with your existing 'brain'.

More complex environments, such as factories, would require multiple 'brains', but once again, with a wireless information capability, you could replace individual 'brains' as needed, keeping the existing equipment infrastructure.

Very interesting idea...


Especially for swapping part...i didnt think of this...

bye!

The following is an excerpt taken from the site<url>http://info.rutgers.edu/Library/Reference/Etext/Impact.of.Science.On.Society.hd/3/5</url>here Isaac answers to a question given below.
Notice how relevent he is,even today.

Question: The first book of yours that I read was I, Robot. In
your opinion, how close are we today to the world you described in
that book?

Answer: Although the book was written in 1939, those robots were very
intelligent and human-like in their capacity. As yet, the robots we
use today are merely computerized arms that can do one specialized
job. So, we're not very close, but we're heading in the right
direction. Although I have never done any work on robots and know
almost nothing about the nuts and bolts, I think that I came close
enough that I am almost the patron saint of robotics. Most of the
people who work in robotics obtained at least some of their early
interest in the field by reading my books. I was the first person to
use the word robotics, and I spoke of the Handbook of Robotic, from
which I quoted my three laws. I said they were from the 56th edition,
in 2058 A.D. Now someone is actually in the process of putting out the
first edition of that book, and they've asked me to write the
introduction. I guess the people who are working in robotics see
themselves moving toward the world I described 40 years ago, and I'm
willing to accept their judgment.


Question: Why do you restrict yourself to looking for Earth-like
planets in the search for technological civilizations, why not
Jupiter-like planets, for instance, or Pluto-like planets?

Answer: If we assume that there can be life even under widely varying
conditions, we make the problem perhaps a little too easy. There is
also the chance that life evolving under such conditions might be so
different from human life in very basic ways that we will not be able
to detect it or to understand that it is a technological civilization
even if we encounter it. As our information and knowledge grow, we
might be able to widen our view to recognize life and civilization of
widely different kinds. But to start with, acknowledging our own
limitations and the fact that we know so little, we are looking for
technological civilizations sufficiently like our own to be perhaps
recognizable. So at the start, but not necessarily forever, we
restrict ourselves to Earthlike planets.

Question: Do you think, because our bodies are fragile and we have
limited life spans, that what we now know as humanity would ever be
replaced by inorganic intelligence?

Answer: I believe that computers have a kind of intelligence which is
extremely different from our own. The computer can do things that we
are particularly ill adapted to do. Humans don't handle rapid
intricate calculations very well, and it's good to have computers do
them. On the other hand, we have the capacity for insight, intuition,
fantasy, imagination, and creativity, which we can't program into our
computers, and it is perhaps not even advisable to try because we do
it so well ourselves. I visualize a future in which we will have both
kinds of intelligence working in cooperation, in a symbiotic
relationship, moving forward faster than either could separately. The
fact that we are so fragile and short lived is an advantage in my way
of thinking. In Robots of Dawn, I compare two civilizations; one is
our own in which people are short lived, and the other is that of our
descendants in which they are long lived. I point out the disadvantage
to the species as a whole of being long lived. I won't repeat the
arguments, because if I don't you may storm the bookstores out of
sheer curiosity to see what I've said.


Question: One of the great themes of science fiction is the settlement
of other planets. Is there any place in this solar system or nearby
that might be habitable?

Answer: As far as we know, there is no worid in our solar system that
is habitable by human beings without some form of artificial help. The
Moon and Mars, which come the closest to being tolerable, will require
us to build underground cities or dome cities, and if we venture on
the surface, we will have to wear space suits. This is not to say that
it will not be possible someday to terraform such worlds and to make
them habitable; but I honestly don't know if it will be worth it for
us to do so. As to planets circling other stars, we do not really know
of such planets in detail. We suspect their existence, and we figure
statistically that a certain number of them ought to be habitable, but
we have yet to observe any evidence of such a thing. It is still very
much in the realm of speculation.


Question: You made the analogy between the migration from Europe at
the turn of the century and possible future migrations to space
stations and other planets. It has been shown that as a result of our
technology, people in this country are taller, heavier, better built,
and able to set new records in endurance and physical capabilities.
Would you speculate about the effect that living in space stations
might have on the human body and its evolutionary potential?

Answer: It is hard to tell. I suspect that people will make the
environment of these space settlements as close to that of Earth as
possible. But in one respect, they will have problems; there is no way
that they can imitate Earth's gravitational field. They can produce a
substitute by making the space settlement rotate, so that the
centrifugal effect will force you against the inner surface and mimic
the effects of gravity. But it won't be a perfect imitation; there
won't be a Coriolis effect and, also as you approach the axes of
rotation, the gravitational effect will become weaker. The people who
will live in a space settlement will be exposed to variations in the
gravitational effect far greater than any you can possibly feel on the
surface of the Earth. This may give rise to all sorts of physiological
changes in human beings. I don't know what they will be; we can't know
until we actually try living in space. So far, people have been
subjected to essentially zero gravity for as long as 7 months at a
time without apparently permanent ill effects. But human beings have
never been born at zero gravity or under varying gravitational
conditions; they have never developed and grown up under such
conditions, and we can't be sure what the effects will be. From an
optimistic standpoint, I suppose that under such conditions human
beings will develop a greater tolerance of gravitational effects than
they now possess. This will further prepare them for life in the
universe, whereas we ourselves have been specifically evolved and
conditioned for life in one very specialized place in the galaxy. The
overall effect may be to strengthen the human species; at least, I'd
like to think so. The future will tell us if that is so.


Question: In your opinion, when will there be solar power stations in
orbit and manned ventures to Mars, considering the technological leaps
with the Space Shuttle and the Soviet's Salyut space stations?

Answer: It is hard to say when solar power stations in space will be
developed. It's up to the human governments that control the money and
the manpower. If we begin to cooperate and make a wholesale attempt,
we could have solar power stations in space before the 21st century
was very old. In other words, someone as young as the person who asked
me this question, may see space stations by the time he is
middle-aged. But on the other hand, if we choose not to do it, then we
may never have these stations in space. The choice is ours. We can
choose to develop space or we can choose world destruction. I'm at a
loss to state in words how desirable the first alternative is and how
likely the second alternative is.


Question: What kind of timetable do you envision for humanity's
exploration of space, and what good or harm do you think is done by
prospace groups?

Answer: Well, we can't expect things to happen too quickly. The
region that we now call the United States was being settled for nearly
two centuries before this country came into existence. We've
celebrated our bicentennial as a nation, but in a little over 20 years
we're going to have to celebrate the tetracentennial of our existence
as a community on American soil, from the establishment of Jamestown
in 1607. If it took nearly two centuries to settle the United States
to nationhood, it might take that long to establish a space community
strong enough to be independent of the Earth. On the other hand,
things move more quickly now; we're more advanced. It may take less
than a century to do so if we really try hard. As for the effects that
prospace organizations might have, I'm not a sociologist so I just
don't know. I'm in favor of prospace organizations doing their best to
persuade human beings to support space exploration. I don't know how
that can be bad.


Question: Assuming that we do not annihilate ourselves, what is your
view of how life on Earth will evolve, both humans and other life
forms?

Answer: You must understand that evolution naturally is a very slow
process and human beings can well live for 100,000 years without many
serious changes. On the other hand, we are now developing methods of
genetic engineering which will, perhaps, be able to wipe out certain
inborn diseases, or correct them and improve various aspects of the
human condition. I don't know how we will develop or what we will
choose to do; it's impossible to predict.


Question: How long do you think it will be before people live in outer
space?

Answer: That's entirely up to us. In a way, we've had people living in
outer space already, ever since the first Russian cosmonaut spent 1
1/2 hours in space. We have now had people living in outer space for 7
months at a time; in fact, one Soviet cosmonaut lived in outer space
for 12 months over a period of 18 months. So we've had people living
in outer space already, and I'm sure we'll have more and more of them
for longer and loner periods of time.

U.S. GOVERNMENT PRINTING OFFICE: 1985Ñ470-563

Library of Congress Cataloging in Publication Data

Burke, James, 1936-

The impact of science on society.

(NASA SP; 482)

Series of lectures given at a public lecture series sponsored by NASA
and the College of William and Mary in 1983.

l. Science - Social aspects - Addresses, essays, lectures. 1. Bergman,
Jules. II. Asimov, Isaac, 1920- . III. United States. National
Aeronautics and Space Administration. IV. College of William and
Mary. V. Title. VI. Series.
Q175.55.B88 1985

303.4'83 84-14159

For sale by the Superintendent of Documents, U.S. Government Printing
Office Washington, D.C. 20402

Science and technology have had a major impact on society, and their
impact is growing. By drastically changing our means of communication,
the way we work, our housing, clothes, and food, our methods of
transportation, and, indeed, even the length and quality of life
itself, science has generated changes in the moral values and basic
philosophies of mankind.

Beginning with the plow, science has changed how we live and what we
believe. By making life easier, science has given man the chance to
pursue societal concerns such as ethics, aesthetics, education, and
justice; to create cultures; and to improve human conditions. But it
has also placed us in the unique position of being able to destroy
ourselves.

To celebrate the 25th anniversary of the National Aeronautics and
Space Administration (NASA) in 1983, NASA and The College of William
and Mary jointly sponsored a series of public lectures on the impact
of science on society. These lectures were delivered by British
historian James Burke, ABC TV science editor and reporter Jules
Bergman, and scientist and science fiction writer Dr. Isaac Asimov.
These authorities covered the impact of science on society from the
time of man's first significant scientific invention to that of
expected future scientific advances. The papers are edited transcripts
of these speeches. Since the talks were genera!ly given
extemporaneously, the papers are necessarily informal and may,
therefore, differ in style from the authors' more formal works.

As the included audience questions illustrate, the topic raises
far-reaching issues and concerns serious aspects of our lives and
future.

Donald P. Hearth
Former Director
NASA Langley Research Center


bye!

A more recent extrapolation is given by Dr. Ray Kurzweil in his book "The age of spiritual machines". We are only 40 years away if the present development continues and we have not reduced our civilization to dust.

zion,

Thanks, I knew I could depend on you posting the first speech somewhere. (I read the second one first) Isaac Assimov (?) has always been a favorite of mine.

Crazy, is it not? The man goes about writting for a living and finds that he is someday to be immortalized in history, awarded an honorary membership in Mensa (plus chairman), and that now they are trying to somehow program into robots his 3 laws of robotics that he used to set up his stories.

Just goes to show that things are not always as they seem and no one can predict the future in any extent.

Thanks for the post.

Hey Wet1,
The man is simply brilliant and all time favorite of mine.i heard that in foundation Novels that he wrote,he fantasised being Hari Seldon...:)

his innovative ideas are astonishing for his own time.i mean look at his time frame,1939 and he is talking about computers connectivity etc.talk about nostradamus!,he was the real one...


bye!

Several years ago, I heard, the Foundation series will be made into movies. I am still waiting....

PS: I have his book on Bible. It is illuminating...

Hi KM,

In the foundation series,specifically in the Foundation edge,Isaac talks about fusion of brain and computer.he demonstratoes it in the begining.
a sort of a computer is there,he touches it(I mean Golan Trevize)and there is a direct connection made to his brain via his hands.the computer analyses the thoughts of the man processes it.:cool:

i"ll quote the exact part later,i dont have it now.
And the only capable guys who can convert foundation series into Movies,as far as i think are WB.Lets hope they do that in the near future...

bye!

PS:Whats this book like,i mean skeptic point of biew or informative,analytic(positive,i mean)??...:confused:

wondering...


bye!

Highly informative. That is my source when people discuss the king james version. He goes to the Hebrew source and explains the meaning of the words and how some words/meanings have changed over the years. Quite interesting if you really want to know for accuracy.

I am not a fan of any organized religion for what they claim and not what they really are - social rules to live by.

Okay lets start a little prematuredly and take a plunge into what exactly is robotics,and what is their purpose etc.
1.1 What is the definition of a 'robot'?

"A reprogrammable, multifunctional manipulator designed to move material,
parts, tools, or specialized devices through various programmed motions for
the performance of a variety of tasks"
Robot Institute of America, 1979
Obviously, this was a committee-written definition. It's rather dry and
uninspiring. Better ones for 'robotics' might include:
Force through intelligence.
Where AI meet the real world.
Webster says: An automatic device that performs functions normally ascribed to
humans or a machine in the form of a human.



[1.2] Where did the word 'robot' come from?
The word 'robot' was coined by the Czech playwright Karel Capek (pronounced
"chop'ek") from the Czech word for forced labor or serf. Capek was reportedly
several times a candidate for the Nobel prize for his works and very influential
and prolific as a writer and playwright. Mercifully, he died before the Gestapo
got to him for his anti-Nazi sympathies in 1938.
The use of the word Robot was introduced into his play R.U.R. (Rossum's
Universal Robots) which opened in Prague in January 1921. The play was an
enormous success and productions soon opened throughout Europe and the US.
R.U.R's theme, in part, was the dehumanization of man in a technological
civilization. You may find it surprising that the robots were not mechanical in
nature but were created through chemical means. In fact, in an essay written in
1935, Capek strongly fought that this idea was at all possible and, writing in
the third person, said:
"It is with horror, frankly, that he rejects all responsibility for the idea
that metal contraptions could ever replace human beings, and that by means of
wires they could awaken something like life, love, or rebellion. He would deem
this dark prospect to be either an overestimation of machines, or a grave
offence against life."
[The Author of Robots Defends Himself - Karl Capek, Lidove noviny, June 9, 1935,
translation: Bean Comrada]
There is some evidence that the word robot was actually coined by Karl's brother
Josef, a writer in his own right. In a short letter, Capek writes that he asked
Josef what he should call the artifical workers in his new play. Karel suggests
Labori, which he thinks too 'bookish' and his brother mutters "then call them
Robots" and turns back to his work, and so from a curt response we have the word
robot.
R.U.R is found in most libraries. The most common English translation is that of
P. Selver from the 1920's which is not completely faithful to the original. A
more recent and accurate translation is in a collection of Capek's writings
called Towards the Radical Center published by Catbird Press in North Haven, CT.
tel: 203.230.2391
The term 'robotics' refers to the study and use of robots. The term was coined
and first used by the Russian-born American scientist and writer Isaac Asimov
(born Jan. 2, 1920, died Apr. 6, 1992). Asimov wrote prodigiously on a wide
variety of subjects. He was best known for his many works of science fiction.
The most famous include I Robot (1950), The Foundation Trilogy (1951-52),
Foundation's Edge (1982), and The Gods Themselves (1972), which won both the
Hugo and Nebula awards.
The word 'robotics' was first used in Runaround, a short story published in
1942. I, Robot, a collection of several of these stories, was published in 1950.
Asimov also proposed his three "Laws of Robotics", and he later added a 'zeroth
law'.
Law Zero:
A robot may not injure humanity, or, through inaction, allow humanity to come
to harm.
Law One:
A robot may not injure a human being, or, through inaction, allow a human
being to come to harm, unless this would violate a higher order law.
Law Two:
A robot must obey orders given it by human beings, except where such orders
would conflict with a higher order law.
Law Three:
A robot must protect its own existence as long as such protection does not
conflict with a higher order law.
An interesting article on this subject:
Clarke, Roger, "Asimov's Laws for Robotics: Implications for Information
Technology", Part 1 and Part 2, Computer, December 1993, pp. 53-61 and Computer,
January 1994, pp.57-65.
The article is an interesting discussion of his Laws and how they came to be in
his books, and the implications for technology today and in the future.



[1.3] When did robots, as we know them today, come into existence?
The first industrial modern robots were the Unimates developed by George Devol
and Joe Engelberger in the late 50's and early 60's. The first patents were by
Devol for parts transfer machines. Engelberger formed Unimation and was the
first to market robots. As a result, Engelberger has been called the 'father of
robotics.'
Modern industrial arms have increased in capability and performance through
controller and language development, improved mechanisms, sensing, and drive
systems. In the early to mid 80's the robot industry grew very fast primarily
due to large investments by the automotive industry. The quick leap into the
factory of the future turned into a plunge when the integration and economic
viability of these efforts proved disastrous. The robot industry has only
recently recovered to mid-80's revenue levels. In the meantime there has been an
enormous shakeout in the robot industry. In the US, for example, only one US
company, Adept, remains in the production industrial robot arm business. Most of
the rest went under, consolidated, or were sold to European and Japanese
companies.
In the research community the first automata were probably Grey Walter's machina
(1940's) and the John's Hopkins beast. Teleoperated or remote controlled devices
had been built even earlier with at least the first radio controlled vehicles
built by Nikola Tesla in the 1890's. Tesla is better known as the inventor of
the induction motor, AC power transmission, and numerous other electrical
devices. Tesla had also envisioned smart mechanisms that were as capable as
humans. An excellent biography of Tesla is Margaret Cheney's Tesla, Man Out of
Time, Published by Prentice-Hall, c1981.
SRI's Shakey navigated highly structured indoor environments in the late 60's
and Moravec's Stanford Cart was the first to attempt natural outdoor scenes in
the late 70's. From that time there has been a proliferation of work in
autonomous driving machines that cruise at highway speeds and navigate outdoor
terrains in commercial applications.
Articles on the history of personal robots:
What ever happened to ... Personal Robots? by Stan Veit The Computer Shopper,
Nov 1992 v12 n11 p794(2)
What ever happened to ... Personal Robots? (part 2) by Stan Veit Computer
Shopper, April 1993 v13 n4 p702(2)
I have the text to these online but am trying to find out if I can include these
as part of the FAQ or as separate files that are ftpable.

This is a continuation of above as i thought the above reply became larger.
The following was compiled from Caltech servers.Interesting information isnt it?
[9] What is a Robot Architecture?
================================================== ===================
A robot 'architecture' primarily refers to the software and hardware framework
for controlling the robot. A VME board running C code to turn motors doesn't
really constitute an architecture by itself. The development of code modules and
the communication between them begins to define the architecture.
Robotic systems are complex and tend to be difficult to develop. They integrate
multiple sensors with effectors, have many degrees of freedom and must reconcile
hard real-time systems with systems which cannot meet real-time deadlines
[Jones93]. System developers have typically relied upon robotic architectures to
guide the construction of robotic devices and for providing computational
services (e.g., communications, processing, etc.) to subsystems and components.
These architectures, however, have tended thus far to be task and domain
specific and have lacked suitability to a broad range of applications. For
example, an architecture well suited for direct teleoperation tends not to be
amenable for supervisory control or for autonomous use.
One recent trend in robotic architectures has been a focus on behavior-based or
reactive systems. Behavior based refers to the fact that these systems exhibit
various behaviors, some of which are emergent [Man92]. These systems are
characterized by tight coupling between sensors and actuators, minimal
computation, and a task-achieving "behavior" problem decomposition.
The other leading architectural trend is typified by a mixture of asynchronous
and synchronous control and data flow. Asychronous processes are characterized
as loosely coupled and event-driven without strict execution deadlines.
Synchronous processes, in contrast, are tightly coupled, utilize a common clock
and demand hard real-time execution.



Subsumption/reactive references
Arkin, R.C., Integrating Behavioral, Perceptual, and World Knowledge in Reactive
Navigation, Robotics & Autonomous Systems, 1990
Brooks, R.A., A Robust Layered Control System for a Mobile Robot, IEEE Journal
of Robotics and Automation, March 1986.
Brooks, R.A., A Robot that Walks; Emergent Behaviors from a Carefully Evolved
Network, Neural Comutation 1(2) (Summer 1989)
Brooks, Rod, AI Memo 864: A Robust Layered Control System For a Mobile Robot.
Look in ftp://publications.ai.mit.edu/
Brooks, Rod, AI Memo 1227: The Behavior Language: User's Guide. look in
ftp://publications.ai.mit.edu/
Connell, J.H., A Colony Architecture for an Artificial Creature, MIT Ph. D.
Thesis in Electrical Engineering and Computer Science, 1989.
Erann Gat, et al, Behavior Control for Robotic Exploration of Planetary Surfaces
To be published in IEEE R &A. FTPable.
ftp://robotics.jpl.nasa.gov/pub/gat/bc4pe.rtf



Insect-based control schemes
Randall D. Beer, Roy E. Ritzmann, and Thomas McKenna, editors, Biological Neural
Networks in Invertebrate Neuroethology and Robotics, Academic Press, 1993.
Hillel J. Chiel, et al, Robustness of a Distributed Neural Network Controller
for Locomotion in a Hexapod Robot, IEEE Transactions on Robotics and Automation,
8(3):293-303, June, 1992.
Joseph Ayers and Jill Crisman, Biologically-Based Control of Omnidirectional Leg
Coordination, Proceedings of the 1992 IEEE/RSJ International Conference on
Intelligent Robots and Systems, pp. 574-581.



Asynchronous/synchronous
(i.e., "traditional", "top-down", etc.)
Amidi, O., Integrated Mobile Robot Control, CMU-RI-TR-90-17, Robotics Institute,
Carnegie Mellon University, 1990.
Albus, J.S., McCain, H.G., and Lumia, R., NASA/NBS Standard Reference Model for
Telerobot Control System Architecture (NASREM) NIST Technical Note 1235, NIST,
Gaithersburg, MD, July 1987.
Butler, P.L., and Jones, J.P., A Modular Control Architecture for Real-Time
Synchronous and Asynchronous Systems, Proceedings of SPIE
Fong, T.W., A Computational Architecture for Semi-autonomous Robotic Vehicles,
AIAA Computing in Aerospace conference, AIAA 93-4508, 1993.
Lin, L., Simmons, R., and Fedor, C., Experience with a Task Control Architecture
for Mobile Robots, CMU-RI-TR 89-29, Robotics Institute, Carnegie Mellon
University, December 1989.
Schneider, S.A., Ullman, M.A., and Chen, V.W., ControlShell: A Real-time
Software Framework, Real-Time Innovations, Inc., Sunnyvale, CA 1992.
Stewart, D.B., Real-Time Software Design and Analysis of Reconfigurable
Multi-Sensor Based Systems, Ph.D. Dissertation, 1994 Dept. of Electrical and
Computer Engineering, Carnegie Mellon University, Pittsburgh. Available online
at STEWART_PHD_1994.ps.Z It's 180+ pages.
Stewart, D.B., M. W. Gertz, and P. K. Khosla, Software Assembly for Real-Time
Applications Based on a Distributed Shared Memory Model, in Proc. of the 1994
Complex Systems Engineering Synthesis and Assessment Technology Workshop (CSESAW
'94), Silver Spring, MD, pp. 217-224, July 1994

More to follow...

bye!

Sensor Based Motion Planning ResearchSensor Based Motion Planning
``Sensor Based Planning'' incorporates sensor information, reflecting the
current state of the environment, into a robot's planning process, as opposed to
classical planning , where full knowledge of the world's geometry is assumed to
be known prior to the planning event. Sensor based planning is important
because: (1) the robot often has no a priori knowledge of the world; (2) the
robot may have only a coarse knowledge of the world because of limited memory;
(3) the world model is bound to contain inaccuracies which can be overcome with
sensor based planning strategies; and (4) the world is subject to unexpected
occurrences or rapidly changing situations.
There already exists a large number of classical path planning methods. However,
many of these techniques are not amenable to sensor based interpretation. It is
not possible to simply add a step to acquire sensory information, and then
construct a plan from the acquired model using a classical technique, since the
robot needs a path planning strategy in the first place to acquire the world
model.
The first principal problem in sensor based motion planning is the find-goal
problem. In this problem, the robot seeks to use its on-board sensors to find a
collision free path from its current configuration to a goal configuration. In
the first variation of the find goal problem, which we term the absolute
find-goal problem, the absolute coordinates of the goal configuration are
assumed to be known. A second variation on this problem is described below.
The second principal problem in sensor based motion planning is sensor-based
exploration, in which a robot is not directed to seek a particular goal in an
unknown environment, but is instead directed to explore the apriori unknown
environment in such a way as to see all potentially important features. The
exploration problem can be motivated by the following application. Imagine that
a robot is to explore the interior of a collapsed building, which has crumbled
due to an earthquake, in order to search for human survivors. It is clearly
impossible to have knowledge of the building's interior geometry prior to the
exploration. Thus, the robot must be able to see, with its on-board sensors, all
points in the building's interior while following its exploration path. In this
way, no potential survivors will be missed by the exploring robot. Algorithms
that solve the find-goal problem are not useful for exploration because the
location of the ``goal'' (a human survivor in our example) is not known. A
second variation on the find-goal problem that is motivated by this scenario and
which is an intermediary between the find-goal and exploration problems is the
recognizable find-goal problem. In this case, the absolute coordinates of the
goal are not known, but it is assumed that the robot can recognize the goal if
it becomes with in line of sight. The aim of the recognizable find-goal problem
is to explore an unknown environment so as to find a recognizable goal. If the
goal is reached before the entire environment is searched, then the search
procedure is terminated.
In prior work we developed a scheme to solve one type of exploration problem. As
a byproduct, the algorithm can then also solve both variations of the find-goal
problem. The algorithm is based on the Generalized Voronoi Graph (GVG), which is
a roadmap. We have developed an incremental approach to constructing the GVG of
an unknown environment strictly from sensor data. We only assume that the robot
has a dead reckoning system and on board sensors that measure distance and
direction to nearby obstacles.
In collaboration with JPL, we have been developing algorithms for the autonomous
navigation of future Mars Rover vehicles. These algorithms (the "WedgeBug" and
"RoverBug" algorithms) are the sensor-based analogies to the classical tangent
graph algorithm, but assume no apriori knowledge of the robot's environment, and
also take the limited field-of-view of the rover's cameras into account. See
this page for more detail and some fancy figures related to this project.
Our current research activities center around how to incorporate uncertainty
into sensor-based planning.

<color=blue>Grasp analysis research</color>
---------------------------------------------------------------------
Grasp Analysis/Planning ResearchGrasp Analysis and Planning Research
We are motivated by a class of important robotic planning problems which are not
handled by current motion-planning systems. Examples are a ``snake-like'' robot
that crawls inside a tunnel by embracing against its sides, or a limbed robot
(analogous to a ``monkey'') that climbs a truss structure by pushing and
pulling. In these examples, the robot is an articulated mechanism whose motions
must be planned so as to achieve high-level goals. However, the robot's motion
is generated by the reaction forces which arise from stably bracing and/or
pushing against the environment. These interaction forces must be planned and
controlled so as to achieve stability of the robot mechanism. It should be noted
that the practically important industrial work-holding or ``fixturing'' problem
is a special case of this class of problems. Multi-fingered grasping and
manipulation is also a related problem. For example, during finger gaiting, the
finger tip reaction forces are used to stably secure the grasped object.
In all of these cases, the interaction forces must be planned and controlled so
as to achieve stability of the robot mechanism. In this proposal, we are
primarily concerned with planning and maintaining quasistatic stability . That
is, in motion where the inertial effects due to the moving parts of the robot
are small relative to the forces-torques of interaction between the robot and
its environment. The quasistatic assumption is immediately applicable to
planning the ``hand-hold'' states (analogous to the hand-holds used by rock
climbers between dynamically moving states) where the grasped object, or the
robot mechanism in the dual case, is at a static equilibrium. Moreover, if the
mechanism's motion between these static states is sufficiently ``slow,'' then
the quasistatic assumption will hold throughout.
Quasistatic motion planning problems are especially attractive for two reasons.
First, these problems are a natural middle ground between classical path
planning and tasks that involve the full dynamics of the robot and the objects
it manipulates, such as hopping, running, or juggling. Second, there is a vast
array of robotic tasks that fall within this category.
To date, our work has focused on developing a basic mobility theory to describe
the mobility of multiply contacting bodies. We have recently extended the theory
to include the effects of compliance, friction, and gravity. Our current efforts
are focused on using the basic methodology to develop quasi-static motion
planning techniques and algorithms for optimal grasp and fixture selection.


<color=blue>Hyper redundant Robotics research</color>
================================================== ===================
Hyper-Redundant Robotics ResearchMedical Applications of Robots
The focus of our work is on the applications of robotics to minimally invasive
medical diagnosis and therapy. Minimally invasive medical techniques are aimed
at reducing the amount of extraneous tissue which must be damaged during
diagnostic or surgical procedures, thereby reducing patient recovery time,
discomfort, and deleterious side effects. Arthroscopic knee surgery is one of
the most widely known example.
We are currently developing, in collaboration with Dr. Warren Grundfest at
Cedars Sinai Hospital, a miniature "snake-like" robot for minimally invasive
traversal of the human gastro-intestinal system. A television camera will allow
the physician to visually inspect the intestinal lining. Additional diagnostic
measurements, such as temperature, pressure, and acidity, can be made with a
variety of on-board micro-sensors. In addition to diagnostic applications, the
device may ultimately be capable assisting in therapeutic procedures as well
We also have recently initiated a collaboration with Dr. Michael Levy of
Children's Hospital (Los Angeles) to develop a new generation of articulated
endoscopes for brain surgery.

More to Follow...


bye!

Modular Robot ResearchModular Robotics Systems
================================================== ==========
The kinematic performance of a conventional robotic mechanism is determined by
its kinematics parameters and its structural topology. For a given set of tasks,
the robot designer chooses these factors during the initial design phase so as
to satisfy the given task requirements. However, it is difficult or impossible
to design a single robot which can meet all task requirements in some
applications. For example, consider the robotic construction of a radio antenna
on the moon's surface. The robotic system must be able to excavate soil,
transport material, assemble parts, inspect constructed assemblies, etc. It is
difficult to design a single robot which is simultaneously strong enough, nimble
enough, and accurate enough for all of these tasks. In this kind of situation it
might be advantageous to deploy a modular robotic system which can be
reassembled into different configurations which are individually well suited to
the diverse task requirements. By a modular robotic system we mean one in which
various subassemblies, at the level of links and joints, can be easily separated
and reassembled into different configurations.
In the deployment of a modular system, one can imagine the module rearrangement
and reassembly process to occur in two ways. First, a human operator can
physically rearrange the modules, and human intuition can be used to determine
the best system configuration for a given task. However, for physically remote
applications, such as robotic lunar construction, the modular system must be
physically able to reconfigure itself. More importantly, there must be a
correspondingly automated way in which to determine a sufficient or optimal
arrangement of the modules to satisfy task criteria. Our work has been devoted
to this latter subject, which has not yet been well addressed in the literature.

To automatically determine a sufficient or optimal arrangement of the system
modules for a given task, one might try a ``generate-and-test'' procedure in
which all possible assembly configurations of the modular set are generated, and
then each assembly configuration is tested against the task requirements to
determine its sufficiency or optimality. However, due to symmetries in module
geometry and robot structural topology, many different assembly configurations
will have the same kinematic properties. Thus, a brute force enumeration of all
module assemblies will result in the generation of many functionally identical
candidate structures. This is undesirable from a computational complexity point
of view, as it leads to many unnecessary test procedures.
We have developed a systematic methodology to enumerate the unique, or
non-isomorphic, assembly configurations of a set of modules. This method is
based on the symmetry properties of the modules and a graph representation of
the robot's structural topology. We introduce an Assembly Incidence Matrix (AIM)
to represent a robot assembly configuration and its associated kinematic graph.
Equivalence relationships are defined on the AIMs using graph isomorphisms and
the symmetric rotation group of individual link modules. AIMs in the same
equivalence class represent isomorphic robots. This method is also useful when
designing a modular robotic system, as it can answer the important question:
``what is the set of uniquely different robots that I can construct from a given
set of modules?''

Robotic Locomotion Research
================================================== ================
Our current work is aimed at developing a more unified theory for the analysis
and control of robotic locomotion. Our investigation of a more unified approach
began with undulatory locomotion. Undulatory robotic locomotion is the process
of generating net displacements of a robotic mechanism via periodic internal
mechanism deformations that are coupled to continuous contstraints between the
mechanism and its environment. Actuatable wheels, tracks, or legs are not
necessary. In general, undulatory locomotion is ``snake-like'' or ``worm-like,''
and includes our study of hyper-redundant robotic systems. However, there are
examples, such as the Snakeboard, which do not have biological counterparts.
From a mechanics perspective, undulatory systems are often characterized as
Lagrangian systems which exhibit symmetries and which are subject to
nonholonomic kinematic constraints. The interplay between the conserved
quantities which would arise from the symmetries (in the absence of nonholonomic
constraints) and the constraints is fundamental to the locomotion process.
Toward this end, we have been developing a control theory for mechanical systems
with symmetries and constraints.
More recently, we have been extending our basic framework for undulatory
locomotion in two directions. First, the basic theory can be extended to systems
with discontinuous contstraints (such as legged systems) by modeling such
systems on stratified sets (see the applied control theory section). Second,
preliminary work has shown that mechanics of a number of aquatic locomotion
schemes also fit into the same framework. See this page for descriptions,
pictures, and videos of our fish work. This page also has some details on our
robot fish work.

Sensor indicates where, and how firmly, a gripper has touched an object.
NASA's Jet Propulsion Laboratory, Pasadena, California

A touch sensor for robot hands provides information about the shape of a grasped object and the force exerted by the gripper on the object. Pins projecting from the sensor create electrical signals when pressed against the object. The tactile sensor (see figure) is packaged in a small, rugged box that fits on the gripper pad. The projecting pins are arranged in a regular matrix on one face of the box. The inner ends of the pins bear on individual circuit elements. An element may be a switch that turns on when a pin is pushed and makes contact with it, or it may be a variable resistor, the conductance of which increases with the force on the pin. The prototype box is milled from a solid slab of aluminum. In it rests a printed-circuit board carrying the switch electrodes (or pressure-sensitive resistors) and the common electrode. Insulating gaps separate the electrodes from the surrounding electrode plane. Covering the printed-circuit board is a plastic insulating spacer, which confines the pins laterally. On the spacer is a rubber spring sheet. The pins pass through the rubber sheet, which restores the pins to their normal positions when a tactile force is removed. Since the holes in the spring sheet are smaller than the heads and feet of the pins, the sheet confines the pins axially. The sensing pins are electrically and mechanically separated from each other. The circuit for each pin is well defined and independent of the circuits for other pins; crosstalk is thus reduced to a minimum. The rubber spring sheet provides an effective seal around each pin and around the box wall. The sensitive portions of the sensor are deep in the box, protected from the environment; grease, dirt, and fumes have little effect on these portions. Since the box bottom supports the printed-circuit board. the board and the pins are protected from damage by overpressure and overtravel.


Point of Contact:
Howard C. Primus
Jet Propulsion Laboratory
4800 Oak Grove Drive
818-248-2638


Touch Sensor Responds to Contact Pressure
================================================== =================
A pressure sensor for a mechanical hand gives better feedback of the gripping force and more-sensitive indication of when the hand contacts an object. Optical fibers bring light into cells on the gripping surface. Light is reflected from a flexible covering into other fibers leading to detectors. Distortion due to tactile pressure changes the amount of reflected light. The new device is superior to previous sensors. For example, television or other direct-viewing systems are not sensitive to contact pressure, and the contact area is often hidden from view. Electrical sensors are subject to electrical noise, especially at the low signal levels associated with low contact pressure. Optical sensors have been used to detect proximity or contact but not contact pressure. The new optical sensor is illustrated in the figure. The sensing surface of the hand is divided into cells by opaque partitions. An optical fiber brings light into each cell from a lamp, light-emitting diode, or other source. Another fiber carries light from the cell to a detector; for example, a photodiode or phototransistor. The cells are covered by an elastic material with a reflective interior surface. The rest of the cell is coated with a nonreflective material. As shown in the figure, pressure against a cell cover causes a distortion, which changes the internal reflection of light. The change is sensed by the detector, and the output signal informs the operator of contact. The greater the pressure and distortion, the greater is the change in light reflection. Thus, grip pressure can be sensed using analog circuitry. If only a touch indication is desired, a threshold detector can be included in the electronics. In an automatic manipulator, the detector signal could control the manipulator movements. The cells can be arranged such that those in each row share one light source, while those in each column share one detector. This reduces the number of sources and detectors and facilitates scanning. For example, a 10-by-10 matrix would have 100 sensing points while requiring only 10 sources and 10 detectors. The array can be scanned by sequentially pulsing sources and detectors.

Point of Contact:
Antal Bejczy
Mail Stop 198-219
Jet Propulsion Laboratory
4800 Oak Grove Drive
Pasadena, CA 91109
818-354-4568
bejczy@telerobotics.jpl.nasa.gov

Position Estimation Using Visual Landmarks
Estimating position and orientation is a fundamental capability required for many mobile robot tasks and is critical for completing long-range traverses and accurate reconnaissance on planetary surfaces.
Simply put, the problem for robots, when on a mission or task, is to be able to estimate their position and orientation using visual landmarks and internal maps. This is the same problem that people face, for example, when competing in the sport of orienteering. Conventional landmark navigation fixes the position of the competitor, with respect to known landmarks at the intersection of several position surfaces. For mobile robots, the idea is to implement, as a supporting technology, the ability to estimate their position using visual landmarks. In an ideal situation, the robot would stop, look around, take in all the features of the landscape, and then calculate its position.

There are three basic techniques for finding one's location: measurement of two bearings, measurement of one bearing and one distance, and measurement of two distances. The first technique, measurement of two bearings is the most attractive because it avoids the challenges of measuring depth or range, and it capitalizes on the relatively high angular resolution of standard cameras and lenses used in the robots.

The two-bearing problem formalizes as follows:

Let (x, y) represent the location of the robot in a fixed, external reference frame W. Let p1, . . . , pn be points representing locations in W of the map landmark points. Let r1, . . . , rk be the rays emanating from (x, y) to the landmarks. A ray represents the direction in which a landmark feature is observed, but does not entail distance information.

The problem: given a set of n landmark points and k rays, find all of the poses Q such that each ray pierces at least one landmark point.

An algorithm that searches for pairings of rays and points solves this problem. The minimum number of pairings for a unique solution to exist is three. First, the search considers only cases of three rays to determine candidate solutions, then, additional rays are used to verify the candidates. The computational complexity of the algorithm is 0 (n^3).

This algorithm has been extended by introducing probability distributions on the rays and landmark points. In this statistical approach, inferences about position are obtained by maximization of the posterior distributionÑthat is, the probability of all possible explanations of what the robot has measured-for (x, y).

The introduction of probabilities allows the modeling and accommodation of various sources of noise and disturbances (noise and disturbances can be anything that results in error for the robot when estimating its position) but it also introduces some difficulties. Essentially, the posterior distribution of (x, y) involves a summation over all possible pairings of rays and landmarks. This implies an exponential effort in the determination of best pose-that is, the pose that provides the most probable position for the