March 18, 2024, 4:42 a.m. | Carmelo Sferrazza, Dun-Ming Huang, Xingyu Lin, Youngwoon Lee, Pieter Abbeel

cs.LG updates on arXiv.org arxiv.org

arXiv:2403.10506v1 Announce Type: cross
Abstract: Humanoid robots hold great promise in assisting humans in diverse environments and tasks, due to their flexibility and adaptability leveraging human-like morphology. However, research in humanoid robots is often bottlenecked by the costly and fragile hardware setups. To accelerate algorithmic research in humanoid robots, we present a high-dimensional, simulated robot learning benchmark, HumanoidBench, featuring a humanoid robot equipped with dexterous hands and a variety of challenging whole-body manipulation and locomotion tasks. Our findings reveal that …

arxiv benchmark cs.ai cs.lg cs.ro humanoid manipulation type

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