Physical Robot

Physical robotics research centers on developing robots capable of performing complex tasks in real-world environments, focusing on improving control, learning, and safety. Current research emphasizes robust policy evaluation methods beyond simple success rates, the use of reinforcement learning (RL) and imitation learning algorithms for skill acquisition and adaptation, and the development of safe and efficient control strategies, including variable impedance control and impact-invariant control. These advancements are crucial for deploying robots in diverse applications, from healthcare and manufacturing to space exploration, requiring improved sim-to-real transfer and addressing challenges like hardware failures and real-time control.