# AiRLIHockey: Highly Reactive Contact Control and Stochastic Optimal Shooting

arXiv: https://arxiv.org/abs/2401.14964 · HTML: https://mlsanity.com/paper/2401.14964/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 26 Jan 2024.

## Built on by (most cited first, 1 of 1)

- [Robot Air Hockey: A Manipulation Testbed for Robot Learning with Reinforcement Learning](https://mlsanity.com/paper/2405.03113/) (2024)

## Abstract (arXiv)

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.