BEHAVIOR Robot Suite: Streamlining Real-World Whole-Body Manipulation
  for Everyday Household Activities
Authors: name: Yunfan Jiang, name: Ruohan Zhang, name: Josiah Wong, name: Chen Wang, name: Yanjie Ze, name: Hang Yin, name: Cem Gokmen, name: Shuran Song, name: Jiajun Wu, name: Li Fei-Fei

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/