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arXiv · 2503.06402

Reduced-Order Model-Based Gait Generation for Snake Robot Locomotion using NMPC

Adarsh Salagame·Eric Sihite·Milad Ramezani·Alireza Ramezani
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Abstract

This paper presents an optimization-based motion planning methodology for snake robots operating in constrained environments. By using a reduced-order model, the proposed approach simplifies the planning process, enabling the optimizer to autonomously generate gaits while constraining the robot's footprint within tight spaces. The method is validated through high-fidelity simulations that accurately model contact dynamics and the robot's motion. Key locomotion strategies are identified and further demonstrated through hardware experiments, including successful navigation through narrow corridors.

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Adarsh Salagame, Eric Sihite, Milad Ramezani, Alireza Ramezani. 2025-03-09. Reduced-Order Model-Based Gait Generation for Snake Robot Locomotion using NMPC. https://arxiv.org/abs/2503.06402

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