In the real world, animals have evolved the ability to get from point A to B by galloping, crawling and jumping. Now, robots in the virtual world have accomplished something similar.
In new work, researchers have simulated evolution using virtual robots and watched them develop locomotion strategies of their own.
In robot-creating simulations, researchers started with random assortments of four types of tissues -- including two kinds of muscle, soft support tissue and bone. The simulations favored the tissue configurations that traveled the fastest from point A to point B. Then the team allowed the mathematical simulation to run its course over 1,000 generations of robots.
"We see really cool stuff as a result of that, without any interaction from me or anyone else, just this process unfolding itself," Nick Cheney, a member of the research team and a doctoral student at Cornell University, told an audience of reporters Tuesday (May 21) here in midtown Manhattan.
The team dubbed the categories of successful robot design that emerged as the L-Walker, the Incher, the Push-Pull, the Jitter, the Jumper and the Wings. [Super-Intelligent Machines: 7 Robotic Futures]
"I would never come up with anything that looks remotely like that," Cheney said, referring to one of these virtual robots. The bots consist of cubes known as voxels (three-dimensional pixels), which display bright colors signifying different types of tissue.
In these simulations, the virtual robots accomplished something highly unusual for robots: They adapted.
Most robots currently in use in the real world are precisely engineered to work in highly constrained environments, such as manufacturing floors, with their every action hand designed and coded by engineers. As a result, these machines cannot adapt to unfamiliar surroundings.
Unlike human engineers, however, nature is a master at creating creatures that can adapt to and interact with their surroundings. This happens through natural selection, the process by which certain traits give organisms a better chance to survive and thus produce more offspring. Nature thus "selects" these traits to persist in future generations. Cheney and colleagues are striving for a similar process in robotics.