LabUtopia: High-Fidelity Simulation and Hierarchical Benchmark for Scientific Embodied Agents

Jinouwen Zhang (Shanghai Artificial Intelligence Laboratory) · Wanli Ouyang (Shanghai AI Lab) · SHIXIANG TANG (The Chinese University of Hong Kong) · LEI BAI (UNSW, Sydney) · Zhenfei Yin (University of Oxford) · Rui Li (Rochester Institute of Technology) · Zixuan Hu (Peking University) · Wenxi Qu (Shanghai Artificial Intelligence Laboratory) · Sha Zhang (University of Science and Technology of China) · Xuantuo Huang (Peking University) · Hanqing Wang (Shanghai Artificial Intelligence Laboratory) · Tai WANG (The Chinese University of Hong Kong) · Jiangmiao Pang (Shanghai AI Laboratory ) · Wangmeng Zuo (Harbin Institute of Technology) · LINGYU DUAN (Peking University) · Dongzhan Zhou (Shanghai Artificial Intelligence Laboratory)
benchmarking suiteembodied agentsembodied intelligenceexperimental workflowsgeneralizable reasoninghierarchical benchmarkhigh-fidelity simulatorlarge-scale traininglong-horizon planningmobile manipulationmulti-physics interactionsphysical-chemical transformationsprincipled evaluationprocedural generatorsimulation suitetask complexity

Scientific embodied agents play a crucial role in modern laboratories by automating complex experimental workflows.Compared to typical household environments, laboratory settings impose significantly higher demands on perception of physical-chemical transformations and long-horizon planning, making them an ideal testbed for advancing embodied intelligence.However, its development has been long hampered by the lack of suitable simulator and benchmarks.In this paper, we address this gap by introducing LabUtopia, a comprehensive simulation and benchmarking suite designed to facilitate the development of generalizable, reasoning-capable embodied agents in laboratory settings. Specifically, it integrates i) LabSim, a high-fidelity simulator supporting multi-physics and chemically meaningful interactions; ii) LabScene, a scalable procedural generator for diverse scientific scenes; and iii) LabBench, a hierarchical benchmark spanning five levels of complexity from atomic actions to long-horizon mobile manipulation. LabUtopia supports 30 distinct tasks and includes more than 200 scene and instrument assets, enabling large-scale training and principled evaluation in high-complexity environments.We demonstrate that LabUtopia offers a powerful platform for advancing the integration of perception, planning, and control in scientific-purpose agents and provides a rigorous testbed for exploring the practical capabilities and generalization limits of embodied intelligence in future research. Project web page: https://rui-li023.github.io/labutopia-site/