MaskedManipulator: Versatile Whole-Body Manipulation

• URL: http://arxiv.org/abs/2505.19086v2
• Date: Sat, 20 Sep 2025 17:43:37 GMT
• Title: MaskedManipulator: Versatile Whole-Body Manipulation
• Authors: Chen Tessler, Yifeng Jiang, Erwin Coumans, Zhengyi Luo, Gal Chechik, Xue Bin Peng,
• Abstract summary: We introduce MaskedManipulator, a generative control policy distilled from a tracking controller trained on large-scale human motion capture data.<n>This two-stage learning process allows the system to perform complex interaction behaviors, while providing intuitive user control over both character and object motions.
• Score: 38.02818493367002
• License: http://creativecommons.org/licenses/by-nc-sa/4.0/
• 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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