Unity RL Playground: A Versatile Reinforcement Learning Framework for Mobile Robots
On the map: Deep reinforcement learning methods → RL for robot locomotion and manipulation
Abstract (arXiv)
This paper introduces Unity RL Playground, an open-source reinforcement learning framework built on top of Unity ML-Agents. Unity RL Playground automates the process of training mobile robots to perform various locomotion tasks such as walking, running, and jumping in simulation, with the potential for seamless transfer to real hardware. Key features include one-click training for imported robot models, universal compatibility with diverse robot configurations, multi-mode motion learning capabilities, and extreme performance testing to aid in robot design optimization and morphological evolution. The attached video can be found at https://linqi-ye.github.io/video/iros25.mp4 and the code is coming soon.
Key facts. No citing papers in the map yet (data through 14 Oct 2026). Placed in RL for robot locomotion and manipulation, one of 15 directions in Deep reinforcement learning methods. Builds on 8 of its 10 references that are in the map. First posted on arXiv 7 Mar 2025.
Builds on
8 of 10 references.
References · 8
- 2021Learning to Walk in Minutes Using Massively Parallel Deep Reinforcement Learningcited by 512
- 2022Learning robust perceptive locomotion for quadrupedal robots in the wildcited by 382
- 2023Orbit: A Unified Simulation Framework for Interactive Robot Learning Environmentscited by 295
- 2018Unity: A General Platform for Intelligent Agentscited by 236
- 2023ANYmal Parkour: Learning Agile Navigation for Quadrupedal Robotscited by 152
- 2025MuJoCo Playgroundcited by 78
- 2024Humanoid-Gym: Reinforcement Learning for Humanoid Robot with Zero-Shot Sim2Real Transfercited by 53
- 2022Advanced Skills through Multiple Adversarial Motion Priors in Reinforcement Learningcited by 37
Built on by
Not cited yet.
Similar, not cited
Close in wording, no citation either way
- 2025RSL-RL: A Learning Library for Robotics Research
- 2024SERL: A Software Suite for Sample-Efficient Robotic Reinforcement Learning
- 2025Taxonomy and Trends in Reinforcement Learning for Robotics and Control Systems: A Structured Review
- 2024Reinforcement Learning Within the Classical Robotics Stack: A Case Study in Robot Soccer
- 2024Deep Reinforcement Learning for Robotics: A Survey of Real-World Successes
- 2026Cross-Embodiment Offline Reinforcement Learning for Heterogeneous Robot Datasets
- 2026The Open Ant: A Robot Platform for Reinforcement Learning Research
- 2025Video-Enhanced Offline Reinforcement Learning: A Model-Based Approach