开源低成本轮式机器人系统，实现真实环境零样本部署
Wheeled Lab: Modern Sim2Real for Low-cost, Open-source Wheeled Robotics
- 整合开源仿真与硬件，构建端到端可复现的机器人学习生态
- 在小型遥控车上实现漂移、越障、视觉导航三类前沿零样本策略
- 适合教学科研，降低现代机器人技术入门门槛
强化学习在近期机器人里程碑中发挥了关键作用，但其进展常依赖专有仿真器、昂贵硬件及复杂工具链，导致更广泛社区难以跟进。为弥合科学界与大众间的差距，本文提出Wheeled Lab：一个集成开源轮式机器人与Isaac Lab（主流开源机器人学习与仿真框架）的生态系统。该系统从硬件到软件全程开源且成本低廉。为推动研究与教育，本工作展示了基于Wheeled Lab训练的三类前沿零样本策略：可控漂移、高程越障与视觉导航。相关视频与材料详见：https://uwrobotlearning.github.io/WheeledLab/
原文摘要 · Abstract (English)
Reinforcement Learning (RL) has been pivotal in recent robotics milestones and is poised to play a prominent role in the future. However, these advances can rely on proprietary simulators, expensive hardware, and a daunting range of tools and skills. As a result, broader communities are disconnecting from the state-of-the-art; education curricula are poorly equipped to teach indispensable modern robotics skills involving hardware, deployment, and iterative development. To address this gap between the broader and scientific communities, we contribute Wheeled Lab, an ecosystem which integrates accessible, open-source wheeled robots with Isaac Lab, an open-source robot learning and simulation framework, that is widely adopted in the state-of-the-art. To kickstart research and education, this work demonstrates three state-of-the-art zero-shot policies for small-scale RC cars developed through Wheeled Lab: controlled drifting, elevation traversal, and visual navigation. The full stack, from hardware to software, is low-cost and open-source. Videos and additional materials can be found at: https://uwrobotlearning.github.io/WheeledLab/
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