Agile Locomotion

Agile locomotion in legged robots focuses on developing control algorithms that enable robots to navigate complex and unstructured terrains with speed, dexterity, and robustness comparable to animals. Current research emphasizes learning-based approaches, including reinforcement learning and imitation learning, often combined with model-predictive control and Koopman operator theory to improve safety and predictability. These advancements are significant for expanding the capabilities of robots in challenging environments, with applications ranging from search and rescue to exploration and material handling.