[Submitted on 14 Sep 2026]
Title:ConGraspXL: Controllable Constraint-Conditioned Dexterous Grasping Motion Synthesis
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Abstract:Dexterous grasping is usually conducted for specific tasks, leading to heterogeneous constraints such as specific approach directions, desired contact regions, specified wrist trajectories, and functional hand poses. Our previous work, GraspXL, achieves scalable grasping motion synthesis for diverse objects and hand morphologies, while lacking controllability for synthesis under such various task-driven constraints. In this paper, we propose ConGraspXL, which extends GraspXL with controllable constraint-conditioned grasp motion synthesis that accommodates diverse task-driven constraints and their combinations. We introduce a hierarchical constraint formulation, enable flexible constraint composition with a masked residual interface, and improve control precision with dynamic hand centers and feed-forward wrist guidance. Without losing the strong generalization capabilities of GraspXL, ConGraspXL enables precise and flexible controllability for various individual constraints and their combinations, providing a plug-and-play low-level grasp controller for downstream applications such as whole-body grasp completion, functional grasping, and human-motion imitation.
Comments: This work has been submitted to the IEEE for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessible
Subjects:
Robotics (cs.RO); Computer Vision and Pattern Recognition (cs.CV)
Cite as: arXiv:2609.16319 [cs.RO]
(or arXiv:2609.16319v1 [cs.RO] for this version)
https://doi.org/10.48550/arXiv.2609.16319
arXiv-issued DOI via DataCite (pending registration)
Submission history
From: Hui Zhang [view email] [v1] Mon, 14 Sep 2026 20:35:04 UTC (18,018 KB)
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