4 papers
Decompose and Reorganize: Planning with Primitives and Visuomotor Policies Learned from Demonstrations
Yizhou Chen, Hang Xu, Dongjie Yu +7
Successfully automating dexterous, long-horizon robotic manipulation requires frameworks capable of both high-level reasoning and fine-grained execution. Traditional task and motio…
SSI-Policy: Learning Structured Scene Interfaces for Vision-Language Robotic Manipulation
Kaijun Wang, Zikai Ouyang, Xuping Wu +6
Real-world robotic manipulation demands spatial grounding, task-aware reasoning, and precise control. Learning such capabilities becomes particularly challenging in the low-data re…
MinInter: Minimizing Trajectory Interpolation During Data Augmentation for Imitation Learning
Qingyang Wang, Xingang Liu, Changwei Yao +4
Imitation learning enables robots to acquire complex manipulation skills from demonstrations, but its effectiveness is limited by the cost of collecting high-quality data. Trajecto…
From Video to Control: A Survey of Learning Manipulation Interfaces from Temporal Visual Data
Linfang Zheng, Zikai Ouyang, Chen Wang +2
Video is a scalable observation of physical dynamics: it captures how objects move, how contact unfolds, and how scenes evolve under interaction -- all without requiring robot acti…