6 papers
SimFoundry: Modular and Automated Scene Generation for Policy Learning and Evaluation
Nadun Ranawaka, Josiah Wong, Wei-Lin Pai +15
Training and evaluating robot policies in the real world is costly and difficult to scale. We introduce SimFoundry, a modular and automated system for zero-shot real-to-sim scene c…
MoMaGen: Generating Demonstrations under Soft and Hard Constraints for Multi-Step Bimanual Mobile Manipulation
Chengshu Li, Mengdi Xu, Arpit Bahety +11
Imitation learning from large-scale, diverse human demonstrations has been shown to be effective for training robots, but collecting such data is costly and time-consuming. This ch…
BEHAVIOR Robot Suite: Streamlining Real-World Whole-Body Manipulation for Everyday Household Activities
Yunfan Jiang, Ruohan Zhang, Josiah Wong +7
Real-world household tasks present significant challenges for mobile manipulation robots. An analysis of existing robotics benchmarks reveals that successful task performance hinge…
robosuite: A Modular Simulation Framework and Benchmark for Robot Learning
Yuke Zhu, Josiah Wong, Ajay Mandlekar +6
robosuite is a simulation framework for robot learning powered by the MuJoCo physics engine. It offers a modular design for creating robotic tasks as well as a suite of benchmark e…
Automated Creation of Digital Cousins for Robust Policy Learning
Tianyuan Dai, Josiah Wong, Yunfan Jiang +5
Training robot policies in the real world can be unsafe, costly, and difficult to scale. Simulation serves as an inexpensive and potentially limitless source of training data, but…
BEHAVIOR Vision Suite: Customizable Dataset Generation via Simulation
Yunhao Ge, Yihe Tang, Jiashu Xu +20
The systematic evaluation and understanding of computer vision models under varying conditions require large amounts of data with comprehensive and customized labels, which real-wo…