BEHAVIOR Robot Suite: Streamlining Real-World Whole-Body Manipulation for Everyday Household Activities
About
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/
Related benchmarks
| Task | Dataset | Result | Rank | |
|---|---|---|---|---|
| Mobile Manipulation | SetTable | Open Fridge Success Rate27 | 12 | |
| Robot Manipulation and Navigation | RoboCasa Manipulation Navigation | PnP C2S Success Rate0.00e+0 | 6 | |
| Mobile Manipulation | ManiSkill-HAB TidyHouse | Pick All Success Rate0.8 | 5 | |
| Mobile Manipulation | ManiSkill-HAB PrepareGroceries | Pick All Success Rate0.8 | 5 | |
| Mobile Robot Manipulation | RoboCasa Mobile Manipulation | PnP C2S Success Rate0.00e+0 | 5 | |
| Inference Efficiency Comparison | Efficiency Evaluation Setup | Inference Time (ms)370 | 3 |