They learned to walk more rapidly than robots with fixed body forms. And, in their final form, they’d developed a more robust gait than those which had learned to walk using upright legs from the beginning.
“This paper shows that body change, morphological change, actually helps us design better robots,” Bongard says. “That’s never been attempted before.”
Bongard started with computer simulations of robots that change in this way.
Some of the creatures begin flat to the ground; others have splayed legs, a bit like a lizard’s. Others ran the full set of simulations with upright legs, like mammals.
Bongard found that those which progressed from slithering to wide legs and, finally, to upright legs, ultimately perform better, getting to the desired behavior faster.
“The snake and reptilian robots are, in essence, training wheels,” says Bongard. “They allow evolution to find motion patterns quicker, because those kinds of robots can’t fall over. So evolution only has to solve the movement problem, but not the balance problem, initially. Then gradually, over ,it’s able to tackle the balance problem after already solving the movement problem.”
The changing robots were not only faster in getting to the final goal, but afterwards were more able to deal with challenges they hadn’t before faced, like efforts to tip them over.
Bongard is unsure why this is, but thinks it’s because controllers learned to maintain the desired behavior over a wider range of sensor-motor arrangements. It seems that learning to walk while flat, squat, and then upright, gave the evolving robots resilience to stay upright when faced with new disruptions.
“In nature, it’s not that the animal’s body stays fixed and its brain gets better over time,” he says. “In natural evolution, animals’ bodies and brains are evolving together all the time.”
After running 5,000 simulations, Bongard took the task into the real world.
“We built a relatively simple robot, out of a couple of Lego Mindstorm kits, to demonstrate that you actually could do it,” he says. The physical robot is four-legged, like the simulation, but wears a brace on its front and back legs.
The brace gradually tilts the robot as the controller searches for successful movement patterns, so that the legs go from horizontal to vertical, from reptile to quadruped.
“It’s a very simple prototype,” he says, “but it works; it’s a proof of concept.”