Josiah Wong

2025BEHAVIOR Challenge

2025BRS: Whole-Body Manipulation for Everyday Tasks
  

2024Digital Cousins for Robot Learning

2024BVS: Customizable Simulated Dataset Generation
  

2022BEHAVIOR-1K: 1,000-Task Embodied AI Benchmark


2022OSCAR: Data-Driven Operational Space Control
  

2021robomimic: Benchmarking Robot Manipulation Tasks


2021MoMaRT: Mobile Manipulation Robot Teleoperation
 

2021iGibson 1.0: Simulating Large Interactive Scenes
 

2021MART: Multi-Arm Robot Teleoperation
2020robosuite: Robot Learning Simulation Framework
 

 



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

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.


CoRL 2025


[Paper] [Website] [Code]


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