3 papers
cs.RO2026
PhysCaP: Grounding Code-as-Policy Agent with Physics-Informed Exploration
Chen-Yu Lin, Jing-Wen Chen, Hsueh-En Chang +8
We present PhysCaP, a Physics-Informed Code-as-Policy agent for active perception in robotic manipulation. While vision-language-action policies excel at imitating demonstrations,…
cs.AI2025
Learning Skills from Action-Free Videos
Hung-Chieh Fang, Kuo-Han Hung, Chu-Rong Chen +7
Learning from videos offers a promising path toward generalist robots by providing rich visual and temporal priors beyond what real robot datasets contain. While existing video gen…
cs.RO2025
Implicit State Estimation via Video Replanning
Po-Chen Ko, Jiayuan Mao, Yu-Hsiang Fu +5
Video-based representations have gained prominence in planning and decision-making due to their ability to encode rich spatiotemporal dynamics and geometric relationships. These re…