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

Created by
  • Haebom

Author

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

Outline

This paper presents a comprehensive framework, the BEHAVIOR Robot Suite (BRS), to address the challenges of mobile manipulation robots in household tasks. BRS is based on a wheeled robot with a bimanual 4-DoF body, integrating a cost-effective full-body teleoperation interface and a full-body visual-motor policy learning algorithm. BRS is evaluated on five challenging household tasks, encompassing a range of complexities, including long-distance movement, interaction with articulated and deformable objects, and manipulation in tight spaces. It focuses on three core capabilities: bimanual coordination, stable and accurate navigation, and extensive end-effector reach, and argues that it represents a significant step toward enabling real-world full-body manipulation. BRS is provided as open source.

Takeaways, Limitations

Takeaways:
A novel framework for improving the performance of mobile robots in domestic tasks: BRS.
Integrating a cost-effective whole-body teleoperation interface with a whole-body visual motor policy learning algorithm.
Successful assessment of five household tasks of varying complexity
Improving research accessibility and promoting collaborative research through open source disclosure
Limitations:
Further validation of the generality and representativeness of the five tasks presented is needed.
BRS's performance has not been compared and analyzed with other robotic systems or algorithms.
Further research is needed on the algorithm's scalability and adaptability to diverse environments.
Lack of evaluation of long-term stable operation
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