Quadrupedal Robot

Quadrupedal robots are increasingly studied for their potential in diverse applications, from assisting humans in various settings to exploring challenging environments. Current research emphasizes developing robust locomotion controllers, often employing reinforcement learning (RL) algorithms, including model-based and model-free approaches, and incorporating advanced sensor fusion techniques for obstacle avoidance and terrain adaptation. This work is significant because it advances the capabilities of legged robots, leading to improved performance in complex tasks and expanding their potential impact across various fields, including search and rescue, construction, and healthcare.