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2026-02-28 03:13:27
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HumanoidBench HumanoidBench: Simulated Humanoid Benchmark for Whole-Body Locomotion and Manipulation Carmelo Sferrazza 1 , Dun-Ming Huang 1 , Xingyu Lin 1 , Youngwoon Lee 1,2 , Pieter Abbeel 1 1 University of California Berkeley, 2 Yonsei University Paper Code 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 state-of-the-art reinforcement learning algorithms struggle with most tasks, whereas a hierarchical learning baseline achieves s...
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