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AiRLIHockey: Highly Reactive Contact Control and Stochastic Optimal Shooting

Published 26 Jan 2024 in cs.RO | (2401.14964v1)

Abstract: 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.

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