Air hockey is a highly reactive game which requires the player to quickly reason over stochastic puck and contact dynamics. We implement a hierarchical framework which combines stochastic optimal control for planning shooting angles and sampling-based model-predictive control for continuously generating constrained mallet trajectories. Our agent was deployed and evaluated in simulation and on a physical setup as part of the Robot Air-Hockey challenge competition at NeurIPS 2023.

翻译：气垫球是一种高度反应性的游戏，要求玩家对随机冰球及接触动力学进行快速推理。我们实现了一种分层框架，该框架结合了用于规划击球角度的随机最优控制与用于连续生成受约束球拍轨迹的基于采样的模型预测控制。我们的智能体在仿真环境和物理平台上进行了部署与评估，作为NeurIPS 2023机器人气垫球挑战赛的一部分。