(ORDO NEWS) — The walking physics of multi-legged animals and robots is simpler than previously thought.
A team of roboticists, physicists and biologists described this discovery in an article published in the Proceedings of the National Academy of Sciences.
“This is important because it will allow roboticists to create much simpler models to describe how robots walk and move around the world,” says paper co-author Nick Gravish, professor in the Department of Mechanical and Aerospace Engineering at the University of California San Diego.
The researchers had previously studied walking ants and wanted to see how their results could be applied to robots. In the course of their work, they discovered a new mathematical relationship between walking, jumping, sliding and swimming in viscous fluids for multi-legged animals and bots.
To study these various animals and robots, the researchers used an algorithm developed by Shai Revzen’s research team at the University of Michigan, which turns complex body movements into shapes.
“This algorithm allows us to create a simple relationship between where you are in a position and where you are going to move next,” notes Gravish.
The researchers found that the same algorithms could be applied to both the ants and the two different types of robots in the study, although the amount of gliding motion while walking varies greatly. Argentine ants also glide a little when walking – only 4.7% of the total range of motion.
By comparison, this percentage of slip is between 12% and 22% for the six-legged BigAnt robot and between 40% and 100% for the six- and twelve-legged multi-legged robots in the study, which occasionally crawl.
Using this model, researchers can predict where an insect or robot will move next, simply based on what pose – or shape – it assumes.
“This provides a universal positioning model that is applicable in all cases where motion is dominated by friction with the environment,” the researchers write.
The mathematics used by scientists is not new. But it was believed that it was applicable only to sliding and swimming in viscous liquids.
The team showed that the same equations apply to multi-legged walking, whether they slide or not. Also, the same rules apply to millimeter-sized insects like ants and meter-sized robots.
“The versatility of this approach could have applications in robot design and motion planning, and provide insight into the evolution and control of leg locomotion,” the researchers emphasize.
They suggest that these universal principles may have implications for understanding major evolutionary transitions, such as the transition from swimming to walking.
Given that walking, even when gliding, follows the same general control principles as viscous swimming, early land animals may already have had the neural network needed to move on land.
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