开源可扩展机器人平台，支持高效家务任务学习
TidyBot++: An Open-Source Holonomic Mobile Manipulator for Robot Learning
- 采用动力万向轮实现全向移动，独立控制平面内所有自由度
- 通过手机遥控采集数据，成功训练出执行多种家务任务的策略
- 低成本、强鲁棒性设计，适合家庭场景机器人学习研究
利用最近在模仿学习方面的进展来推动移动操作任务，需要大量由人类引导的示范数据。本文提出一种开源的低成本、鲁棒且灵活的移动操作机器人设计，可适配任意机械臂，支持广泛的现实家庭移动操作任务。关键在于，该设计采用动力万向轮，使移动底盘具备完全全向运动能力，能够独立且同时控制所有平面自由度。这一特性显著提升底盘灵活性，简化了许多移动操作任务，消除了非全向底盘带来的运动学约束，避免了复杂耗时的动作规划。我们为机器人配备直观的手机遥控操作界面，便于快速获取模仿学习所需的数据。实验中，使用该界面收集数据，并验证所学策略能成功完成多种常见家庭操作任务。
原文摘要 · Abstract (English)
Exploiting the promise of recent advances in imitation learning for mobile manipulation will require the collection of large numbers of human-guided demonstrations. This paper proposes an open-source design for an inexpensive, robust, and flexible mobile manipulator that can support arbitrary arms, enabling a wide range of real-world household mobile manipulation tasks. Crucially, our design uses powered casters to enable the mobile base to be fully holonomic, able to control all planar degrees of freedom independently and simultaneously. This feature makes the base more maneuverable and simplifies many mobile manipulation tasks, eliminating the kinematic constraints that create complex and time-consuming motions in nonholonomic bases. We equip our robot with an intuitive mobile phone teleoperation interface to enable easy data acquisition for imitation learning. In our experiments, we use this interface to collect data and show that the resulting learned policies can successfully perform a variety of common household mobile manipulation tasks.
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