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Ew, a cockroach! But it zips off before the swatter appears. Now, researchers have leveraged the bug’s superb scurrying skills to create a cleverly simple method to assess and improve locomotion in robots.
Normally, tedious modeling of mechanics, electronics, and information science is required to understand how insects’ or robots’ moving parts coordinate smoothly to take them places. But in a new study, biomechanics researchers at the Georgia Institute of Technology boiled down the sprints of cockroaches to handy principles and equations they then used to make a test robot amble about better.
The method told the researchers about how each leg operates on its own, how they all come together as a whole, and the harmony or lack thereof in how they do it. Despite bugs’ and bots’ utterly divergent motion dynamics, the new method worked for both and should work for other robots and animals, too.
The biological robot, the roach, was the far superior runner with neurological signals guiding six impeccably evolved legs. The mechanical robot, a consumer model, had four stubby legs and no nervous system but relied instead for locomotion control on coarse physical forces traveling through its chassis as crude signals to roughly coordinate its clunky gait.
“The robot was much bulkier and could hardly sense its environment. The cockroach had many senses and can adapt better to rough terrain. Bumps as high as its hips wouldn’t slow it down at all,” said Izaak Neveln, the study’s first author, who was a postdoctoral researcher in the lab of Simon Sponberg at Georgia Techduring the study.
The method, or “measure,” as the study calls it, transcended these huge differences, which pervade animal-inspired robotics.
“The measure is general (universal) in the sense that it can be used regardless of whether the signals are neural spiking patterns, kinematics, voltages or forces and does not depend on the particular relationship between the signals,” the study’s authors wrote.
No matter how a bug or a bot functions, the measure’s mathematical inputs and outputs are always in the same units. The measure will not always eliminate the need for modeling, but it stands to shorten and guide modeling and avert anguishing missteps.
Centralization vs. Decentralization
Often a bot or an animal sends many walking signals through a central system to harmonize locomotion, but not all signals are centralized. Even in humans, though locomotion strongly depends on signals from the central nervous system, some neural signals are confined to regions of the body; they are localized signals.
Some insects appear to move with little centralization -- such as stick bugs, also known as walking sticks, whose legs prod about nearly independently. Stick bugs are wonky runners.
“The idea has been that the stick bugs have the more localized control of motion, whereas a cockroach goes very fast and needs to maintain stability, and its motion control is probably more centralized, more clocklike,” Neveln said.
Strong centralization of signals generally coordinates locomotion better. Centralized signals could be code traveling through an elaborate robot’s wiring, a cockroach’s central neurons synching its legs, or the clunky robot's chassis tilting away from a leg thumping the ground thus putting weight onto an opposing leg.
Roboticists need to see through the differences and figure out the interplay of a locomotor’s local and central signals.