Category Archives: Robotics
The Pooping Duck
The quest to create mechanical creatures goes back to the ancient Greeks, but the concept experienced a revival at the end of the Renaissance. Around 1640, Descartes put forth the idea that the human body works like a machine and could be understood as such. The idea that nature can be viewed as a mechanical process was solidified in 1687 when Newton published his Principia. In it, he describes in detail how nature follows mathematical rules. Indeed, Newton viewed the universe as a massive clock built by God and set into motion. These ideas were a precursor to the Industrial Revolution and also made clockwork automata a fad in Europe in the early 18th century.
Jacques Vaucanson [1709-1782] was an unsung hero of the Industrial Revolution. The invention of the mechanical loom is usually credited to Joseph Jacquard, but it was Vaucanson who first came up with the idea of using punchcards to store textile patterns, a technology that would be used in the first computers 200 years later. Vaucanson also build the first functioning automaton, a mechanical flute player that emulated a human being. The lips and fingers of the player moved naturally on the flute, and he painstakingly copied the musculature and breathing of a human. Its breath could be felt emanating from the mouth as it played.
After the success of the flute player, Vaucanson built an automated tambourine player, and finally his most famous work, a mechanical duck in 1738. The duck was made of gilded copper and contained over 400 moving parts hidden from view. The duck could drink, eat, quack, splash about and even defecate. Vaucanson used a new high-tech material, rubber, to design the ducks digestive system, and thus developed the world’s first flexible rubber tube. It was later discovered that the duck did not actually defecate as the “feces” were stored in a separate compartment, but this did not diminish the magnitude of his masterpiece.
Vaucanson was a showman and toured througout Europe with his duck, charging admission and wowing audiences with his creation. No-one had ever before seen a mechanism which appeared so alive. He eventually caught the attention of the French government who hired him as inspector of the manufacture of silk. It was during this time he invented the first fully automated loom which used punch cards, the machine later improved upon by Jacquard. The silk workers of Lyon rebelled against Vaucanson’s automatic loom by pelting him with stones in the street, insisting that no machine could replace them. This foreshadowed the later anti-industrial sentiment of the Luddite movement in Britain. Vaucanson’s original automata were lost to history, but a replica of the duck is now kept in the Musee des Automates in Grenoble, France.
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Baby Steps
Passive dynamics is an approach to robotics which uses the momentum of swinging limbs for greater efficiency. A purely passive dynamic robot requires no power at all. It will able down a plank all by itself if it’s configured just right. Of course, in the real world robots can’t be expected to always walk downhill. Ideally, one could combine the efficiency of passive dynamics with some kind of power so it can walk efficiently on a flat surface.
In 2003 at the University of Sussex, Eric Vaughan used artificial evolution to create powered bipedal walkers in simulation. Evolving both the passive dynamic body and the neural control system all at once didn’t work, so the evolution was given some assistance. First, the robot was evolved to walk down an incline passively. As the evolution progressed, the plank was gradually lowered until it was completely horizontal, gradually bringing the neural control system into play. The final result was a robot design that could walk on a flat surface using very little energy, much like a human.
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The Replicators
In 1970, noting the extreme cost of space exploration, the physicist Freeman Dyson proposed a wild idea: send a machine into space that is capable of building copies of itself from materials it finds. This would provide an unlimited production and exploration capacity for a finite cost.
Although just a thought experiment, Dyson’s idea is not as crazy as it sounds. In the early 1980s, NASA funded a series of investigations into cheap space colonization which involved building self-replicating factories on the moon. It’s theoretically possible, but robot factories building more robot factories poses a huge maintenance problem. After all, you’d need an army of repair robots to fix things when they break down. And, who repairs the repair robots?
Eric Drexler, a proponent of nanotechnology, describes a more elegant solution. He envisions tiny, molecular “assemblers” that can build copies of themselves and other items of greater complexity — a bottom-up version of the self-replicating factory idea. He also notes that such technology, if not tamed properly, could replicate out of control consuming all the resources on the planet resulting in the so called Grey Goo Scenario.
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| Copyright Shane Willis |
Thought experiments aside, some researchers have succeeded in building primitive, yet practical self-replicating machines. Adrian Bowyer from the University of Bath developed a rapid prototyping machine called RepRap that can make most of the parts necessary to build… another RepRap machine.
Bowyer’s RepRap project is now replicating “in the wild”. On November 30, 2008, the first user outside the lab used one of the machines to produce and sell a set of RepRap parts to someone else. Being a prototyping machine, RepRap is not limited to copying itself. It has been used to create ordinary objects including a coathook, a pair of sandals, and a fly swatter. The potential for such a machine is vast and is fortunately not likely to turn the world into goo anytime soon.
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Nature’s Best
When building a robot that emulates an existing animal or other life form, engineers must accept the humble truth: nature always does it better. You just can’t compete with billions of years of evolution. Consider the agility of a simple house fly, or the fact that certain moths can identify pheromones when there are only a few molecules present. Some researchers have therefore concluded that it is far more effective to try and interface with some of nature’s technology instead of building it from scratch.
Jose Delgado pioneered the research into electrical brain stimulation at Yale in the 1940s by inserting electrodes into cats and monkeys to evoke responses in the brain. In a famous media stunt in 1963, he fitted a bull with a remote control device which stimulated a specific part of its brain. He stepped into the ring with the bull and let it charge him. At the last second, he activated the stimulator, stopping the bull in its tracks.
Since then, the military has gained interest in this technology as it could be used on insects for surveillance purposes. Various DARPA funded projects have succeeded in controlling insects and beetles, getting their wings to flap at different speeds based on a computer controlled electrodes inserted into specific parts of their brains. The big problem is trying to design components small enough that can be inserted into an insect’s body without disrupting its flight.
Chuck Higgins from the University of Arizona thinks a better approach is to turn the problem inside out by embedding insects into the robot. If a robot could leverage the chemical sniffing ability of a moth, for example, then it could be used by the military for detecting explosives. Higgins and his team have been able to build a robot that can read visual information directly from its passenger Hawk Moth’s brain using electrodes and amplifiers and send this information back into the robot’s control system. In the future, he’d like to integrate with other parts of the moth brain, including the olfactory system which would give his robots one of the most sophisticated sensory systems available.
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Robo-lobster
Joseph Ayers has a thing for lobsters. He likes to cook them, eat them, and build them. In his book, “Dr. Ayers Cooks With Cognac” he describes several creative lobster recipes from Cajun to Mediterranean and everything in between. His favorite way to eat a lobster is simply dipping the meat in butter accompanied with a glass of chardonnay. And, when it comes to building robot lobsters, he prefers the kind that can wander the sea floor searching for mines.
A biologist and neuroscientist, Dr. Ayers developed his robo-lobster at Northeastern University between 1999 and 2002 with funding from the Office of Naval Research (ONR) and the Defense Advanced Research Projects Agency (DARPA). Working from Northeastern’s Marine Science Center at East Point in Nahant, Massachusetts, Ayers looked to real-life lobsters for inspiration. He notes that lobsters are at the top of the food chain in their environment and so have a good built-in seek-and-destroy mechanism.
His robots are controlled with artificial neural networks, which are used to make subtle decisions such as whether to walk over or around a rock. When it comes to tweaking the design, Ayers always went back to the original, studying the behavior of living lobsters, trying to replicate their behavior. The plastic antennas sense obstacles, the eight legs can propel it in any direction, and the claws and tail keep it stable in turbulent water.
The robo-lobster’s actuators are controlled by Nitinol, otherwise known as “muscle wire”. Nitinol can change shape when a current is passed through it, making it more life-like and less “robotic”. Also, Ayers’ neural networks use Central Pattern Generators (CPGs), specialized neural circuits found in all animal brains that automatically generate a rhythmic patterns. The CPG acts as the source for the robots pattern of locomotion.
The robo-lobster is an excellent example of biomimicry, where ideas from nature are incorporated into robotic designs, however, a practical mission for the robo-lobster has yet to be demonstrated. In addition to finding mines, Ayers notes that it might also be used to measure pollution levels on the ocean floor. The robo-lobster was put on display at the Cooper-Hewitt museum in New York in 2007 as part of its “Design Life Now” exhibit. It was also named one of the Coolest Inventions of 2003 by Time Magazine.
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Resilient Robots
Using artificial evolution to design robots is a powerful technique. The difficult part is writing a simulation of the robot and its physical environment. A simulation is required so tens of thousands of design variations can be automatically tested as the evolution progresses.
What if you didn’t need to write a simulation? Imagine the robot could figure out how to simulate itself. Not only have you saved yourself a lot of programming, but the robot is now very resilient. You could snap off one of its legs, for example, and it would be able to re-simulate itself, and re-evolve a walking strategy.
Hod Lipson from Cornell University’s Computational Synthesis Lab has built such a robotic system. His robot first squirms around on the floor, testing theories about how its own motors work and what its own shape is. This simulation of itself is then used to evolve a walking strategy.
Such a system would be very useful for planetary exploration, where robot engineers may not be readily available to fix problems. If the machine breaks a leg, no problem. Re-simulate, re-evolve, and move on.
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Simple Life
In 1986, the German neuroscientist, Valentino Braitenberg, made an important observation about human psychology. He said, “When we analyze a mechanism, we tend to overestimate its complexity.”
Try following an ant around while it searches for food. You might infer a complex mind that is processing a myriad of difficult decisions. However, the ant’s actions can be explained by a very simple set of rules.
Even so, it’s not always easy to determine what those rules might be, looking in from the outside. Braitenberg therefore concluded that, when studying complex behavior, you must invent your own rules, from the inside looking out. In short, you tinker from the simplest possible starting point and see what emerges.
This line of thought led to his famous book, “Vehicles: Experiments in Synthetic Psychology,” which details a series of thought experiments in which simple mechanisms seemingly exhibit complex behavior.
Consider, for example, Braitenberg’s vehicle #2a. It’s a two-wheeled robot with light sensors. When light on the right side increases, so does the right wheel’s speed. Same with the left side. The result is a robot that avoids light. Cross the wires, and you have a robot that steers and accelerates towards a light source (vehicle #2b). While the simplest of parts comprise both robots, Braitenberg describes the former as “cowardly,” and the latter as “aggressive.”
How about robots that display “love?” Braitenberg’s vehicle #3 adds some inhibitory connections, which cause the robot to approach a light, and then gradually stop to stare at it indefinitely.
Other adjustments can create robots, which Braitenberg describes as “exploring, knowing, displaying instincts, making decisions, having foresight, ego and optimism.” Obviously, these are subjective, anthropomorphic terms, but Braitenberg purposely uses them to make his point: complex behavior can arise from simple mechanisms, IF they are configured just the right way.
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Spring Turkey
The “Spring Turkey” robot was built by Peter Dilworth and Jerry Pratt in 1994 at the MIT Leg Laboratory. The device was a test platform for walking robots that used what is called “Series Elastic Actuation.” Instead of connecting a leg to a motor directly, a spring was inserted between them. Thus, the motor controlled the spring, and the spring controlled the leg. Because the spring can absorb some elastic energy when the robot lands, the robot’s walking became less rigid.
Dilworth and Pratt also simplified the problem by restricting the robot’s motions. This is a standard technique where the robot is tethered to a pole, so that it cannot fall over to the left or right while in motion. “Spring Turkey” is just one of many successful real-life walking robot experiments to come out of the MIT Leg Laboratory.
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House of Horrors
Abandon hope, all ye who enter here. The uncanny valley is the place where “Awww, how cute!” becomes “Aaah! Its alive!”. People, puppets, and stuffed animals live outside the valley. Zombies, bad special effects, and creepy robots live within it. With that, I introduce the Uncanny Valley Awards for Creepiness in Robotics:
Third Place – Eva
Ever since David Hanson decided to make a robot simulacrum of his girlfriend back in 2002, he has been a prodigious creator of creepy robots. His research focuses on simulated emotional responses, animatronic facial expressions, and even the development of an artificial skin. Impressive stuff, yet his creations still land squarely inside the valley. video
Second Place – Geminoid
When it comes to building creepy robots, the Japanese are hands down the absolute masters. Take for example Hiroshi Ishiguro who built a robot in his own likeness. By doing so, he allows us to observe the differences between him and his robot directly, amplifying the valley’s revulsion effect. Nicely done! video (Japanese)
First Place – CB2
It has been said that roboticists tend to be males because they have a Freudian-like procreation envy. The robot called CB2 developed at Osaka University may be a literal manifestation of that theory. A learning “child robot”, CB2 lives in the deep, dark, recesses of the uncanny valley. Combining the demeanor of a zombie with expressions of mentally impaired joy, CB2 is the official king of the valley. Congratulations CB2! video (Japanese)
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Robots That Balance
Have you ever tried to balance a broom on one finger? Humans can do this fairly easily, and so can machines because the control system equations for this “inverted pendulum” system are relatively simple. It turns out that the process of walking and running in animals and robots is very similar to balancing a broom. If you assume the body of the robot is always about to fall over, then the inverted pendulum equations can be used to compute where the legs should be at each moment in order to maintain balance.
Marc Raibert, who founded the MIT Leg Laboratory in the 1980s, used this idea to build a robot with a single leg that could maintain its balance. Although it looked like a hyperactive pogo stick, the “hopper” robot was a success. Expanding on this work, he later moved to two legs, and finally four:
In 2005, Raibert founded Boston Dynamics, makers of the Big Dog military pack robot which uses the same basic concepts for remaining dynamically balanced. In fact, it can stay balanced on slippery surfaces and even remain stable after receiving a sharp kick. Boston Dynamics is funded by DARPA. The pack bots are designed to assist soldiers by following them in the field and can carry up to 120 pounds of supplies across a variety of terrains.
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