不愧是中国机器人，乒乓打得太6了

Core Viewpoint - The article discusses the advancements in humanoid robots, specifically focusing on a table tennis robot developed by Tsinghua University students, showcasing its ability to perform high-level table tennis skills through a combination of hierarchical planning and reinforcement learning [7][8]. Group 1: Robot Performance - The robot can respond with a reaction time of 0.42 seconds and has achieved a maximum of 106 consecutive hits during a match [3][5][23]. - In real-world tests, the robot successfully returned 24 out of 26 balls, achieving a hitting rate of 96.2% and a return rate of 92.3% [21]. Group 2: Technical Framework - The research team proposed a hierarchical framework that separates high-level planning from low-level control, allowing the robot to predict ball trajectories and execute human-like movements [9][11]. - A model-based planner predicts the ball's position, speed, and timing, while a reinforcement learning-based controller generates coordinated movements [10][16]. Group 3: Training Methodology - The robot was trained using a standard table tennis setup, with its hand modified to function as a paddle [13]. - The training incorporated human motion references to encourage the robot to mimic human-like swinging actions [18][19]. Group 4: Challenges in Robotics - Table tennis is highlighted as a challenging sport for robots due to the need for rapid perception, prediction, planning, and execution within a very short time frame [29][30]. - The sport requires agile full-body movements, including quick arm swings, waist rotations, and balance recovery, making it a complex task for humanoid robots [32][33].