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arXiv · 2505.19086

MaskedManipulator: Versatile Whole-Body Manipulation

Chen Tessler·Yifeng Jiang·Erwin Coumans·Zhengyi Luo·Gal Chechik·Xue Bin Peng
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Abstract

We tackle the challenges of synthesizing versatile, physically simulated human motions for full-body object manipulation. Unlike prior methods that are focused on detailed motion tracking, trajectory following, or teleoperation, our framework enables users to specify versatile high-level objectives such as target object poses or body poses. To achieve this, we introduce MaskedManipulator, a generative control policy distilled from a tracking controller trained on large-scale human motion capture data. This two-stage learning process allows the system to perform complex interaction behaviors, while providing intuitive user control over both character and object motions. MaskedManipulator produces goal-directed manipulation behaviors that expand the scope of interactive animation systems beyond task-specific solutions.

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Chen Tessler, Yifeng Jiang, Erwin Coumans, Zhengyi Luo, Gal Chechik, Xue Bin Peng. 2025-05-25. MaskedManipulator: Versatile Whole-Body Manipulation. https://arxiv.org/abs/2505.19086

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