Agile asymmetric multi-legged locomotion: contact planning via geometric mechanics and spin model duality

Fuente: arXiv
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Hauptverfasser: Habala, Jackson, Margolis, Gabriel B., Wang, Tianyu, Bhatt, Pratyush, He, Juntao, Naeem, Naheel, Xu, Zhaochen, Agrawal, Pulkit, Goldman, Daniel I., Luo, Di, Chong, Baxi
Format: Preprint
Veröffentlicht: 2026
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author Habala, Jackson
Margolis, Gabriel B.
Wang, Tianyu
Bhatt, Pratyush
He, Juntao
Naeem, Naheel
Xu, Zhaochen
Agrawal, Pulkit
Goldman, Daniel I.
Luo, Di
Chong, Baxi
author_facet Habala, Jackson
Margolis, Gabriel B.
Wang, Tianyu
Bhatt, Pratyush
He, Juntao
Naeem, Naheel
Xu, Zhaochen
Agrawal, Pulkit
Goldman, Daniel I.
Luo, Di
Chong, Baxi
contents 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 multi-legged locomotion. We use geometric mechanics to reduce contact-rich locomotion planning to a graph optimization problem, and propose a spin model duality framework from statistical mechanics to exploit symmetry breaking and guide optimal gait reorganization. Using this approach, we identify an asymmetric locomotion strategy for a hexapod robot that achieves a forward speed of 0.61 body lengths per cycle (a 50% improvement over conventional gaits). The resulting asymmetry appears at both the control and hardware levels. At the control level, the body orientation oscillates asymmetrically between fast clockwise and slow counterclockwise turning phases for forward locomotion. At the hardware level, two legs on the same side remain unactuated and can be replaced with rigid parts without degrading performance. Numerical simulations and robophysical experiments validate the framework and reveal novel locomotion behaviors that emerge from symmetry reforming in high-dimensional embodied systems.
format Preprint
id arxiv_https___arxiv_org_abs_2602_09123
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Agile asymmetric multi-legged locomotion: contact planning via geometric mechanics and spin model duality
Habala, Jackson
Margolis, Gabriel B.
Wang, Tianyu
Bhatt, Pratyush
He, Juntao
Naeem, Naheel
Xu, Zhaochen
Agrawal, Pulkit
Goldman, Daniel I.
Luo, Di
Chong, Baxi
Robotics
Systems and Control
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 multi-legged locomotion. We use geometric mechanics to reduce contact-rich locomotion planning to a graph optimization problem, and propose a spin model duality framework from statistical mechanics to exploit symmetry breaking and guide optimal gait reorganization. Using this approach, we identify an asymmetric locomotion strategy for a hexapod robot that achieves a forward speed of 0.61 body lengths per cycle (a 50% improvement over conventional gaits). The resulting asymmetry appears at both the control and hardware levels. At the control level, the body orientation oscillates asymmetrically between fast clockwise and slow counterclockwise turning phases for forward locomotion. At the hardware level, two legs on the same side remain unactuated and can be replaced with rigid parts without degrading performance. Numerical simulations and robophysical experiments validate the framework and reveal novel locomotion behaviors that emerge from symmetry reforming in high-dimensional embodied systems.
title Agile asymmetric multi-legged locomotion: contact planning via geometric mechanics and spin model duality
topic Robotics
Systems and Control
url https://arxiv.org/abs/2602.09123