Robot dog walks on tough terrain with two legs, withstands kicks

Researchers at the University of Hong Kong’s ArcLab have developed a quadruped robot capable of walking on two legs using a bio-inspired controller called TumblerNet, powered by Deep Reinforcement Learning. This system mimics human balance by integrating estimators for the robot’s center of mass and center of pressure into a closed-loop control, enabling seamless transitions between quadrupedal and bipedal locomotion. The robot can respond to various movement commands, including turning and walking in circles, demonstrating advanced adaptability. The robot’s robustness is notable, as it maintains balance on challenging terrains such as foam pads, loose rocks, sand, and even a beach environment. It withstands external disturbances like pushes and kicks without requiring a separate recovery model, and it can automatically recover from falls caused by obstacles. These capabilities highlight the potential advantages of bipedal robots over traditional quadrupeds, especially for navigating human environments and performing complex tasks in caregiving, disaster response, and human-robot collaboration. The researchers