Athletic Mobile Manipulator System for Robotic Wheelchair Tennis
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Abstract (arXiv)
Athletics are a quintessential and universal expression of humanity. From French monks who in the 12th century invented jeu de paume, the precursor to modern lawn tennis, back to the K'iche' people who played the Maya Ballgame as a form of religious expression over three thousand years ago, humans have sought to train their minds and bodies to excel in sporting contests. Advances in robotics are opening up the possibility of robots in sports. Yet, key challenges remain, as most prior works in robotics for sports are limited to pristine sensing environments, do not require significant force generation, or are on miniaturized scales unsuited for joint human-robot play. In this paper, we propose the first open-source, autonomous robot for playing regulation wheelchair tennis. We demonstrate the performance of our full-stack system in executing ground strokes and evaluate each of the system's hardware and software components. The goal of this paper is to (1) inspire more research in human-scale robot athletics and (2) establish the first baseline for a reproducible wheelchair tennis robot for regulation singles play. Our paper contributes to the science of systems design and poses a set of key challenges for the robotics community to address in striving towards robots that can match human capabilities in sports.
Key facts. Cited by 7 papers in the map (data through 7 Oct 2026). First posted on arXiv 5 Oct 2022.
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Citing papers per year: 2024: 3; 2025: 3; 2026: 1.
7 papers.
- 2025BOSS: Benchmark for Observation Space Shift in Long-Horizon Taskcited by 7
- 2024Multi-Camera Asynchronous Ball Localization and Trajectory Prediction with Factor Graphs and Human Posescited by 4
- 2024Bridging the gap between Learning-to-plan, Motion Primitives and Safe Reinforcement Learningcited by 4
- 2025Integrating Learning-Based Manipulation and Physics-Based Locomotion for Whole-Body Badminton Robot Controlcited by 2
- 2024A Retrospective on the Robot Air Hockey Challenge: Benchmarking Robust, Reliable, and Safe Learning Techniques for Real-world Roboticscited by 1
- 2025Towards Learning Scalable Agile Dynamic Motion Planning for Robosoccer Teams with Policy Optimizationcited by 0
- 2026Towards Professional Tennis Styles for Humanoid Robots with Adaptive Motion Planning and Trackingcited by 0
- 2026Towards Professional Tennis Styles for Humanoid Robots with Adaptive Motion Planning and Tracking20 Aug 2026
- 2025Integrating Learning-Based Manipulation and Physics-Based Locomotion for Whole-Body Badminton Robot Control24 Apr 2025
- 2025BOSS: Benchmark for Observation Space Shift in Long-Horizon Task21 Feb 2025
- 2025Towards Learning Scalable Agile Dynamic Motion Planning for Robosoccer Teams with Policy Optimization8 Feb 2025
- 2024A Retrospective on the Robot Air Hockey Challenge: Benchmarking Robust, Reliable, and Safe Learning Techniques for Real-world Robotics8 Nov 2024
- 2024Bridging the gap between Learning-to-plan, Motion Primitives and Safe Reinforcement Learning26 Aug 2024
- 2024Multi-Camera Asynchronous Ball Localization and Trajectory Prediction with Factor Graphs and Human Poses30 Jan 2024