BEHAVIOR机器人套件：优化现实世界全身操控，助力日常家务活动

摘要

现实世界中的家务任务对移动操作机器人提出了重大挑战。通过对现有机器人基准测试的分析发现，成功完成任务依赖于三项关键的整体控制能力：双手协调、稳定且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，但由此带来的系统复杂性进一步增加了视觉运动策略学习的难度。为应对这些挑战，我们推出了BEHAVIOR机器人套件（BRS），这是一个面向多样化家务任务中整体操作的综合性框架。BRS基于一款配备4自由度躯干的双手机器人，集成了一套经济高效的整体遥操作接口用于数据收集，以及一种新颖的学习整体视觉运动策略的算法。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项核心能力，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狭小空间内的操作。我们相信，BRS集成的机器人实体、数据收集接口及学习框架，标志着在实现日常家务任务中整体操作方面迈出了重要一步。BRS已在https://behavior-robot-suite.github.io/开源。

English

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/

BEHAVIOR机器人套件：优化现实世界全身操控，助力日常家务活动

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

摘要

Summary

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