Walking is like slithering: A unifying, data-driven view of locomotion
| Autor: | Dan Zhao, Brian Bittner, Glenna Clifton, Nick Gravish, Shai Revzen |
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| Rok vydání: | 2022 |
| Předmět: | |
| Zdroj: | Proceedings of the National Academy of Sciences. 119 |
| ISSN: | 1091-6490 0027-8424 |
| DOI: | 10.1073/pnas.2113222119 |
| Popis: | Legged movement is ubiquitous in nature and of increasing interest for robotics. Most legged animals routinely encounter foot slipping, yet detailed modeling of multiple contacts with slipping exceeds current simulation capacity. Here we present a principle that unifies multilegged walking (including that involving slipping) with slithering and Stokesian (low Reynolds number) swimming. We generated data-driven principally kinematic models of locomotion for walking in low-slip animals (Argentine ant, 4.7% slip ratio of slipping to total motion) and for high-slip robotic systems (BigANT hexapod, slip ratio 12 to 22%; Multipod robots ranging from 6 to 12 legs, slip ratio 40 to 100%). We found that principally kinematic models could explain much of the variability in body velocity and turning rate using body shape and could predict walking behaviors outside the training data. Most remarkably, walking was principally kinematic irrespective of leg number, foot slipping, and turning rate. We find that grounded walking, with or without slipping, is governed by principally kinematic equations of motion, functionally similar to frictional swimming and slithering. Geometric mechanics thus leads to a unified model for swimming, slithering, and walking. Such commonality may shed light on the evolutionary origins of animal locomotion control and offer new approaches for robotic locomotion and motion planning. |
| Databáze: | OpenAIRE |
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