mlsanityData to 14 Oct 2026

BricksRL: A Platform for Democratizing Robotics and Reinforcement Learning Research and Education with LEGO

arXiv 2406.17490 ↗First posted 25 Jun 2024cs.RO cs.LGcited by 0

On the map: Deep reinforcement learning methods → RL for robot locomotion and manipulation

Abstract (arXiv)

We present BricksRL, a platform designed to democratize access to robotics for reinforcement learning research and education. BricksRL facilitates the creation, design, and training of custom LEGO robots in the real world by interfacing them with the TorchRL library for reinforcement learning agents. The integration of TorchRL with the LEGO hubs, via Bluetooth bidirectional communication, enables state-of-the-art reinforcement learning training on GPUs for a wide variety of LEGO builds. This offers a flexible and cost-efficient approach for scaling and also provides a robust infrastructure for robot-environment-algorithm communication. We present various experiments across tasks and robot configurations, providing built plans and training results. Furthermore, we demonstrate that inexpensive LEGO robots can be trained end-to-end in the real world to achieve simple tasks, with training times typically under 120 minutes on a normal laptop. Moreover, we show how users can extend the capabilities, exemplified by the successful integration of non-LEGO sensors. By enhancing accessibility to both robotics and reinforcement learning, BricksRL establishes a strong foundation for democratized robotic learning in research and educational settings.

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 26 of its 47 references that are in the map. First posted on arXiv 25 Jun 2024.

Builds on

26 of 47 references.

References · 26

  1. 2018Addressing Function Approximation Error in Actor-Critic Methodscited by 2,417
  2. 2018Soft Actor-Critic Algorithms and Applicationscited by 1,240
  3. 2018QT-Opt: Scalable Deep Reinforcement Learning for Vision-Based Robotic Manipulationcited by 743
  4. 2019Solving Rubik's Cube with a Robot Handcited by 734
  5. 2020Learning Quadrupedal Locomotion over Challenging Terraincited by 604
  6. 2022DayDreamer: World Models for Physical Robot Learningcited by 400
  7. 2022VIP: Towards Universal Visual Reward and Representation via Value-Implicit Pre-Trainingcited by 395
  8. 2024Mobile ALOHA: Learning Bimanual Mobile Manipulation with Low-Cost Whole-Body Teleoperationcited by 391
  9. 2016Learning Hand-Eye Coordination for Robotic Grasping with Deep Learning and Large-Scale Data Collectioncited by 316
  10. 2021MT-Opt: Continuous Multi-Task Robotic Reinforcement Learning at Scalecited by 229
  11. 2023A Survey of Imitation Learning: Algorithms, Recent Developments, and Challengescited by 148
  12. 2023Learning Agile Soccer Skills for a Bipedal Robot with Deep Reinforcement Learningcited by 133
14 more
  1. 2021Dropout Q-Functions for Doubly Efficient Reinforcement Learningcited by 114
  2. 2022A Walk in the Park: Learning to Walk in 20 Minutes With Model-Free Reinforcement Learningcited by 83
  3. 2019ROBEL: Robotics Benchmarks for Learning with Low-Cost Robotscited by 72
  4. 2024ALOHA 2: An Enhanced Low-Cost Hardware for Bimanual Teleoperationcited by 63
  5. 2023TorchRL: A data-driven decision-making library for PyTorchcited by 60
  6. 2023AirExo: Low-Cost Exoskeletons for Learning Whole-Arm Manipulation in the Wildcited by 47
  7. 2023Barkour: Benchmarking Animal-level Agility with Quadruped Robotscited by 41
  8. 2022Learning Torque Control for Quadrupedal Locomotioncited by 29
  9. 2023Grow Your Limits: Continuous Improvement with Real-World RL for Robotic Locomotioncited by 24
  10. 2022Learning Low-Frequency Motion Control for Robust and Dynamic Robot Locomotioncited by 12
  11. 2022HeRo 2.0: A Low-Cost Robot for Swarm Robotics Researchcited by 4
  12. 2020RealAnt: An Open-Source Low-Cost Quadruped for Education and Research in Real-World Reinforcement Learningcited by 3
  13. 2022A Low-Cost Robot Science Kit for Education with Symbolic Regression for Hypothesis Discovery and Validationcited by 2
  14. 2021Stanford Pupper: A Low-Cost Agile Quadruped Robot for Benchmarking and Educationcited by 1

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  1. 2024PLANRL: A Motion Planning and Imitation Learning Framework to Bootstrap Reinforcement Learning
  2. 2024DIPPER: Direct Preference Optimization to Accelerate Primitive-Enabled Hierarchical Reinforcement Learning
  3. 2026The Open Ant: A Robot Platform for Reinforcement Learning Research
  4. 2022How to Spend Your Robot Time: Bridging Kickstarting and Offline Reinforcement Learning for Vision-based Robotic Manipulation
  5. 2024Deep Reinforcement Learning for Robotics: A Survey of Real-World Successes
  6. 2026Nautilus: From One Prompt to Plug-and-Play Robot Learning
  7. 2026Teaching Machine Learning Fundamentals with LEGO Robotics
  8. 2025Benchmarking Massively Parallelized Multi-Task Reinforcement Learning for Robotics Tasks