Multi Legged Robot
Multi-legged robots, inspired by the locomotion of centipedes and other arthropods, are being developed to navigate complex and challenging terrains. Current research focuses on improving their maneuverability through advanced control strategies, often employing wave-based models of body undulation and leg coordination, sometimes enhanced by reinforcement learning algorithms to adapt to varied environments. These advancements aim to enhance the robots' robustness, particularly in self-righting and obstacle negotiation, leading to applications in search-and-rescue, agriculture, and space exploration.
Papers
Effective self-righting strategies for elongate multi-legged robots
Erik Teder, Baxi Chong, Juntao He, Tianyu Wang, Massimiliano Iaschi, Daniel Soto, Daniel I Goldman
Steering Elongate Multi-legged Robots By Modulating Body Undulation Waves
Esteban Flores, Baxi Chong, Daniel Soto, Dan Tatulescu, Daniel I. Goldman
Addition of a peristaltic wave improves multi-legged locomotion performance on complex terrains
Massimiliano Iaschi, Baxi Chong, Tianyu Wang, Jianfeng Lin, Juntao He, Daniel Soto, Zhaochen Xu, Daniel I Goldman