DynamicManip: Enabling Dynamic Manipulation from a Single Static Demonstration
Dynamic manipulation is a critical capability for robots operating in complex and dynamic environments, where robots must interact with objects that are moving or require rapid adjustments. However, learning models for dynamic manipulation tasks face two major challenges: (1) the combinatorial complexity of dynamic scenarios leads to substantial data requirements, and (2) rapid variations in dynamics require real-time and accurate policy execution. In this paper, we propose DynamicManip to address these challenges through an efficient data augmentation pipeline and a low-latency imitation policy. We first propose a static-to-dynamic augmentation pipeline that synthesizes diverse dynamic m...
| Authors | Haoran Liao, Pengyue Wang, Shuoyu Chen et al. |
|---|---|
| Primary category | cs.RO |
| Published | 2 August 2026 |
| Last updated at source | 2 August 2026 |
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