arXiv 2503.056522025-08-24cs.ROcs.AIcs.CVcs.LG

BEHAVIOR Robot Suite：简化现实世界日常家务活动的全身操纵

BEHAVIOR Robot Suite: Streamlining Real-World Whole-Body Manipulation for Everyday Household Activities

Stanford University（斯坦福大学）

Yunfan Jiang, Ruohan Zhang, Josiah Wong, Chen Wang, Yanjie Ze, Hang Yin, Cem Gokmen, Shuran Song, Jiajun Wu, Li Fei-Fei

备注：: 9th Conference on Robot Learning (CoRL 2025), Seoul, Korea. Project website: https://behavior-robot-suite.github.io/

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AI总结：

针对现实家务任务中移动操纵机器人面临的挑战，该研究提出BEHAVIOR Robot Suite（BRS）综合框架，基于特定硬件集成遥操作接口与新学习算法，在五项复杂家务任务中验证，推动现实全身操纵发展。

摘要：

现实世界的家务任务对移动操纵机器人提出了重大挑战。对现有机器人基准的分析表明，任务的成功执行取决于三个关键的全身控制能力：双手协调、稳定精确的导航以及广泛的末端执行器可达性。实现这些能力需要精心的硬件设计，但由此产生的系统复杂性进一步加剧了视觉运动策略学习的难度。为应对这些挑战，我们引入了BEHAVIOR Robot Suite（BRS），这是一个用于多样化家务任务中全身操纵的综合框架。BRS基于一款带有4自由度躯干的双手轮式机器人，集成了经济高效的全身遥操作接口用于数据收集，以及一种用于学习全身视觉运动策略的新算法。我们在五项具有挑战性的家务任务上对BRS进行了评估，这些任务不仅强调了上述三种核心能力，还引入了额外的复杂性，如长距离导航、与铰接和可变形物体的交互以及在受限空间中的操纵。我们认为，BRS的集成机器人实体、数据收集接口和学习框架是朝着实现现实世界日常家务全身操纵迈出的重要一步。BRS已开源，地址为https://behavior-robot-suite.github.io/

英文摘要：

Real-world household tasks present significant challenges for mobile manipulation robots. An analysis of existing robotics benchmarks reveals that successful task performance hinges on three key whole-body control capabilities: bimanual coordination, stable and precise navigation, and extensive end-effector reachability. Achieving these capabilities requires careful hardware design, but the resulting system complexity further complicates visuomotor policy learning. To address these challenges, we introduce the BEHAVIOR Robot Suite (BRS), a comprehensive framework for whole-body manipulation in diverse household tasks. Built on a bimanual, wheeled robot with a 4-DoF torso, BRS integrates a cost-effective whole-body teleoperation interface for data collection and a novel algorithm for learning whole-body visuomotor policies. We evaluate BRS on five challenging household tasks that not only emphasize the three core capabilities but also introduce additional complexities, such as long-range navigation, interaction with articulated and deformable objects, and manipulation in confined spaces. We believe that BRS's integrated robotic embodiment, data collection interface, and learning framework mark a significant step toward enabling real-world whole-body manipulation for everyday household tasks. BRS is open-sourced at https://behavior-robot-suite.github.io/

机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。