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.

BricksRL 是一个用于加强学习研究和教育的平台，它通过与 TorchRL 库连接，实现了在现实世界中创建、设计和训练定制的 LEGO 机器人，通过蓝牙双向通信与 LEGO 智能中枢交互，从而实现了 GPU 上的最先进的加强学习训练，为各种 LEGO 构建提供了灵活和高效的扩展方法。