For multi-legged creatures, it’s a lot like sliding

Experimental devices for studying ant freckles are similar to those used in the study. Credit: David Bailot/University of California San Diego

The walking physics of multi-legged animals and robots is simpler than previously thought. This is the discovery described by a team of robotics, physicists and biologists in the September 5 issue of the journal Proceedings of the National Academy of Sciences, In an article titled “Walking Like Slithering: A Unified Data-Driven View of Motion”.

“This is important because it will allow robotics to build much simpler models to describe the way robots walk and move around the world,” said research co-author Nick Gravish, faculty member in the Department of Mechanical and Aerospace Engineering at UCSD. Diego.

The researchers had previously studied the way ants walk and wanted to know how their findings could be applied to robots. In the process, they discovered a new mathematical relationship between walking, jumping, sliding and swimming in the sticky fluids of multilegged animals and robots.

The team studied several colonies of Argentine ants at the University of California, San Diego, and two different types of multi-legged robots at the University of Michigan.






Videos of a walking ant, a walking multi-legged robot, and a walking BigANT robot. Credit: University of California San Diego/University of Michigan

“It’s very easy to study Argentine ants in the lab,” said paper co-author Glenna Clifton, a University of Portland faculty member who did most of the ant research while she was a postdoctoral scientist in the Gravish Lab at UCSD.

Argentine ants are good walkers that can cover long distances on different terrains. These ants also adapt easily to laboratory settings, and quickly rebuild their colonies. The researchers could then motivate them to walk by placing the food in specific places. “These ants will set up paths to find food and follow them,” Clifton said. “They recover quickly and don’t hold a grudge.”

To study these different animals and robots, the researchers used an algorithm developed by the research team Shai Revzen at the University of Michigan, which converts complex body movements into shapes. “This algorithm allows us to establish a simple relationship between the situation you are in and where you will go next,” Gravish said.

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 their gliding motions when walking differed greatly. Argentine ants don’t slip much while walking — only 4.7% of all movement. By contrast, this slip rate ranges from 12% to 22% for the six-legged BigANT robot and 40% to 100% for the multi-legged robots with six to 12 feet in the study, which occasionally crawl.

Using this model, researchers can predict where the insect or robot will next move simply based on the position – or shape – it takes. “This provides a global model of location to be applied when environmental contact dominates movement,” the researchers wrote.

The mathematics the researchers used is not new. But it was understood that mathematics applied only to sliding and swimming in viscous fluids. The team showed that the same equations apply to multi-legged walking, whether the pedestrians are sliding or not. In addition, the same rules apply from millimeter-scale insects, such as ants, to meter-scale robots. One early version of the paper’s title was “Walking Like a Worm”.

“The universality of this approach may have applications in Robot design and motion planning, and provides insight into the evolution and tuning of the two-legged locomotion,” the researchers wrote.

The researchers hypothesize that these universal principles may have implications for understanding key evolutionary transitions, for example from swimming to walking. Given that walking, even with gliding, follows the same general principles of control as sticky swimming, early land animals may already have had neural circuits Necessary to move on the ground.

The physics of walking is simpler than we thought

Researchers Glenna Clifton, of the University of Portland, and Nick Gravish, of the University of California, San Diego, harvest ants on the UCSD campus. Credit: David Bailot/University of California San Diego

The researchers haven’t studied the two-legged creatures, but the model will apply to them as long as they move slowly, have both feet on the ground at the same time, and don’t fall off. (Photo of Michael Jackson walking on the moon.)

The team still has more fine-tuning to do, to understand, for example, the role that frictional forces play in the model.

“Either way, walking can be a lot simpler than we usually think,” Gravish said.


A beaver-inspired way to direct the movements of a one-legged swimming robot


more information:
Walking like sliding: a unified, data-driven view of movement, Proceedings of the National Academy of Sciences (2022). DOI: 10.1073/pnas.2113222119

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