Air Hockey

Air hockey, a dynamic game involving precise puck manipulation, serves as a compelling testbed for advancing robotics research, particularly in reinforcement learning and control. Current research focuses on developing efficient algorithms, such as model-based deep reinforcement learning and stochastic optimal control, to enable robots to learn complex strategies and react quickly to the game's stochastic nature, often incorporating techniques like constraint manifolds for safe and efficient planning. These advancements contribute to a broader understanding of robot learning in high-dimensional, real-time interactive environments, with implications for various manipulation tasks beyond gaming.