# DefFlow: A Goal-Conditioned Framework for Deformable Object Manipulation Based on 3D Point Flows

- Source: arXiv cs.RO
- Published: 2026-10-19T04:00:00.000Z
- RoboHot: https://robohot.news/en/items/thrt9tbggcdpz5id7bw7lvt6t
- Original: https://arxiv.org/abs/2610.22827

## Summary

DefFlow is a goal-conditioned manipulation framework for deformable objects. By jointly predicting the goal-conditioned 3D point flows of the robot and the deformable object from demonstrations, it captures manipulation decisions such as grasping, releasing, and re-grasping, as well as the continuous fine motions required to reach the goal. Across rope, granular media, and cloth settings with diverse initial and target configurations, DefFlow clearly outperforms goal-conditioned action prediction and robot-flow-only baselines on success rate and goal-distance metrics, and it was deployed on a real robot using real point cloud observations and unseen target configurations.