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ConGraspXL advances robotic manipulation by introducing controllable constraint-conditioned motion synthesis, allowing for precise adaptation to specific task-driven constraints like approach directions and wrist trajectories. This development enhances the generalization capabilities of its predecessor, GraspXL, enabling plug-and-play controllers for complex downstream applications such as whole-body grasp completion and human-motion imitation.
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ConGraspXL: Controllable Constraint-Conditioned Dexterous Grasping Motion Synthesis

arXiv2 min read

arXiv:2609.16319v1 Announce Type: new 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.

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.

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

Robotics (cs.RO); Computer Vision and Pattern Recognition (cs.CV)

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)

Full text under the publisher's open licence · 191 words

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