Agile asymmetric multi-legged locomotion: contact planning via geometric mechanics and spin model duality
Jackson Habala, Gabriel B. Margolis, Tianyu Wang, Pratyush Bhatt, Juntao He, Naheel Naeem, Zhaochen Xu, Pulkit Agrawal, Daniel I. Goldman, Di Luo, Baxi Chong

TL;DR
This paper introduces a geometric mechanics and spin model duality framework for multi-legged robot locomotion, enabling the discovery of asymmetric gaits that improve speed and hardware efficiency in hexapods.
Contribution
It develops a principled control framework for multi-legged robots using geometric mechanics and symmetry exploitation, leading to novel asymmetric locomotion strategies.
Findings
Achieved 50% faster forward speed with asymmetric gait
Identified hardware simplifications without performance loss
Validated approach through simulations and experiments
Abstract
Legged robot research is presently focused on bipedal or quadrupedal robots, despite capabilities to build robots with many more legs to potentially improve locomotion performance. This imbalance is not necessarily due to hardware limitations, but rather to the absence of principled control frameworks that explain when and how additional legs improve locomotion performance. In multi-legged systems, coordinating many simultaneous contacts introduces a severe curse of dimensionality that challenges existing modeling and control approaches. As an alternative, multi-legged robots are typically controlled using low-dimensional gaits originally developed for bipeds or quadrupeds. These strategies fail to exploit the new symmetries and control opportunities that emerge in higher-dimensional systems. In this work, we develop a principled framework for discovering new control structures in…
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Taxonomy
TopicsRobotic Locomotion and Control · Modular Robots and Swarm Intelligence · Biomimetic flight and propulsion mechanisms
