2nd Place Solution to the HANDS 2026 Workshop Challenge-Dexterous Grasp Motion Track: Single-Shot Trajectory Warping for Grasp Motion Generation
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Abstract (arXiv)
This report describes our 2nd place solution to the HANDS 2026 workshop challenge (Dexterous Grasp Motion track) in conjunction with ECCV 2026. In this challenge, we address grasp motion generation for the 12-DoF LinkerHand O6, aiming to produce physically plausible reach-and-lift trajectories for unseen objects from randomized initial hand poses in simulation. This task is particularly challenging because each grasp requires a per-step policy to make approximately 70 twelve-dimensional decisions, with errors accumulating over time, while test objects and physical dynamics may differ from those encountered during training. To address these challenges, we propose editing a single successful GraspM3 demonstration instead of generating the motion step by step: a policy observes the object once and outputs a 12-D warp of the demonstration, which is then replayed open-loop. Moreover, we train the warp policy with one-step PPO over all 4,824 training objects in parallel. As a result, our method achieved success rates of 94.61% on the easy track, the highest of all submissions, and 57.18% on the hard track of the private test set.
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References · 7
- 2017Proximal Policy Optimization Algorithmscited by 15,215
- 2016PointNet: Deep Learning on Point Sets for 3D Classification and Segmentationcited by 5,248
- 2015ShapeNet: An Information-Rich 3D Model Repositorycited by 2,897
- 2022Objaverse: A Universe of Annotated 3D Objectscited by 1,540
- 2021Isaac Gym: High Performance GPU-Based Physics Simulation For Robot Learningcited by 998
- 2023DexRepNet: Learning Dexterous Robotic Grasping Network with Geometric and Spatial Hand-Object Representationscited by 16
- 2025DemoGrasp: Universal Dexterous Grasping from a Single Demonstrationcited by 9
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