Quadrupedal Locomotion

Quadrupedal locomotion research aims to enable robots to move efficiently and robustly on diverse terrains, mimicking the agility of animals. Current efforts focus on improving locomotion control through reinforcement learning, often employing model predictive control (MPC) or neural networks (including recurrent and transformer architectures), and integrating advanced perception (e.g., vision, lidar) for terrain awareness and manipulation capabilities. These advancements are significant for expanding the capabilities of robots in challenging environments, with applications ranging from search and rescue to industrial automation and exploration.