日本フィジカルAI新聞

世界のフィジカルAIを、日本語で。

週刊ニュースレター購読
arXiv:2506.19968

Evolutionary Gait Reconfiguration in Damaged Legged Robots

Evolutionary Gait Reconfiguration in Damaged Legged Robots

シェア:XThreadsFacebookLINEはてブBluesky

著者: Sahand Farghdani, Robin Chhabra

分類: cs.RO

原文アブストラクト

Multi-legged robots deployed in complex missions are susceptible to physical damage in their legs, impairing task performance and potentially compromising mission success. This letter presents a rapid, training-free damage recovery algorithm for legged robots subject to partial or complete loss of functional legs. The proposed method first stabilizes locomotion by generating a new gait sequence and subsequently optimally reconfigures leg gaits via a developed differential evolution algorithm to maximize forward progression while minimizing body rotation and lateral drift. The algorithm successfully restores locomotion in a 24-degree-of-freedom hexapod within one hour, demonstrating both high efficiency and robustness to structural damage.