Category Archives: Passive Dynamics
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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Evolution: Creativity Engine
Evolution is an inherently creative process. Left to its own devices, it will automatically generate complex and beautiful forms.
Only three ingredients are required for a runaway evolutionary process to take hold: replication, variation, and selection. In nature, DNA is the replicator. It is able to make high-fidelity copies of itself under the right conditions. Variation comes from occasional errors during the copying process, and selection comes from the environment as some life is better suited to live and reproduce under the extant conditions of the planet than others.
Interestingly, these three ingredients are relatively easy to program into a computer. Replication is something computers do inherently. Copying data from one place to another is their most basic function. Variation is achieved by artificially adding some randomness to the copying process, again trivial for a computer. Selection requires a little more work. The programmer must decide what makes some entities more “fit” than others which usually requires a simulation of some kind. The fitter entities are then given more of a chance to copy themselves.
My masters thesis at the University of Sussex in 2005 was to design running, springy robots in simulation (called Metapets). The design task itself was too difficult to solve on my own due to the complex interaction of the springs and coordination of the limbs although I tried. Eventually, I appealed to evolution to work out the details. The fitness of each robot was determined by how far it moved forward, thus selecting robots for speed.
At the start of the evolutionary process, most robots would just fall down and go into convulsions. Others walked backwards, went in circles, or just stood still. But, after letting evolution run for several weeks, more functional designs gradually emerged, and the longer I ran the simulation, the better the designs became.
Many of the designs that evolved were quirky looking, while others dragged their legs, walked on their elbows, or moved in ways that one would not consider intuitive. Therein lies artificial evolution’s primary caveat: it may provide a means of automatically solving a specific problem in a creative way, but not necessarily the way you intended or expected. When this happens, the evolutionary pressure can be refined by adjusting the “fitness function” which determines each model’s fitness score in the selection step.
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Passive Dynamic Walkers
In the late 80s, Tad McGeer invented the concept of passive dynamics. While doing graduate work at Simon Fraser University, he built a robot that could walk down a plank without power, sensors, or a control system. The robot was built from metal rods, springs, and weights in just the right configuration such that the legs and arms would swing in a coordinated way as it ambled down. It was also able to walk efficiently on a flat surface by giving it a small push. In 2001, Steve Collins from Cornell University build a passive walker based on McGeer’s original model shown in the video below.
The idea of adding power to passive dynamic walkers later inspired other universities to develop their own versions. McGeer demonstrated that a bottom-up approach to robotics must begin with the body. A cleverly designed body can remove the need for high speed computers to control all the leg movements. This approach has still not been widely accepted. For instance, Honda’s Asimo Robot which after 20 years of research and at a cost of $1 million per unit still uses a bulldozer approach of scanning and conquering the environment instead of dynamically interacting with it.
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The Blade Runner
Oscar Pistorius, a.k.a. “The Blade Runner”, had both his legs amputated below the knee when he was 11 months old due to complications from a genetic disorder. The replacement carbon-fiber blades later developed for him turned out to be more efficient than the natural human muscle/tendon system. Thus, his entry into the 2008 Olympics for the men’s 400 meter race caused a minor controversy. Eventually, he was allowed to compete, but failed to qualify. The questions raised about prosthetic advantages in able-bodied competitions remain unresolved.
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