SOURCE-LINKED INTELLIGENCE

DynaForge: Planning-Guided Residual Learning for Dynamic Manipulation Demonstration Generation

arXiv · AI, language, vision and robotics · article · Sep 22, 2026 · UTC

Dynamic object manipulation is essential for robots operating in real-world environments, yet methods for generating high-quality demonstrations remain limited. Methods designed for static tasks do not readily transfer to dynamic settings. Among dynamic demonstration generators, planning-based methods can fail near contact, while DOMINO-style replay simplifies dynamic interactions and may limit the experience available for policy learning. We present DynaForge, a planning-guided framework that learns residual corrections for dynamic manipulation demonstration generation. DynaForge combines low

Read original source ↗ Open in workspace

recordType

paper

region

Global