DexJoCo: A Benchmark and Toolkit for Task-Oriented Dexterous Manipulation on MuJoCo
Summary
DexJoCo introduces a benchmark and toolkit for task-oriented dexterous manipulation in MuJoCo, featuring 11 functional tasks, a low-cost data collection system, and comprehensive evaluations that highlight limitations in current dexterous manipulation policies.
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Paper page - DexJoCo: A Benchmark and Toolkit for Task-Oriented Dexterous Manipulation on MuJoCo
Source: https://huggingface.co/papers/2605.16257 Published on May 15
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Abstract
DexJoCo presents a benchmark and toolkit for dexterous manipulation with 11 functional tasks evaluating tool-use, bimanual coordination, and long-horizon execution, along with a low-cost data collection system and comprehensive model evaluation.
Achieving human-level manipulation requires dexterous robotic hands capable of complex object interactions. Advancing such capabilities further demands standardizedbenchmarks for systematic evaluation. However, existing dexterousbenchmarks lack tasks that reflect the unique manipulation capabilities of dexterous hands over parallel grippers, as well as comprehensive evaluation pipelines. In this paper, we present DexJoCo, abenchmarkandtoolkitfor task-orienteddexterous manipulation, comprising 11functionally grounded tasksthat evaluatetool-use,bimanual coordination,long-horizon execution, and reasoning. We develop a low-cost data collection system and collect 1.1K trajectories across these tasks, with support fordomain randomizationto assess robustness. Webenchmarkmodern models under diverse settings, including visual anddynamics randomization,multi-task training, andaction-head adaptation. Through extensive empirical analysis, we identify several important insights and common limitations of current policies indexterous manipulation, highlighting key challenges for future research in dexterous hand robot learning. Project page available at: https://dexjoco.github.io
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