4 papers
DexMan: Learning Bimanual Dexterous Manipulation from Human and Generated Videos
Jhen Hsieh, Kuan-Hsun Tu, Kuo-Han Hung +1
We present DexMan, an automated framework that converts human visual demonstrations into bimanual dexterous manipulation skills for humanoid robots in simulation. Operating directl…
Information Seeking for Robust Decision Making under Partial Observability
Djengo Cyun-Jyun Fang, Tsung-Wei Ke
Explicit information seeking is essential to human problem-solving in practical environments characterized by incomplete information and noisy dynamics. When the true environmental…
See, Point, Fly: A Learning-Free VLM Framework for Universal Unmanned Aerial Navigation
Chih Yao Hu, Yang-Sen Lin, Yuna Lee +7
We present See, Point, Fly (SPF), a training-free aerial vision-and-language navigation (AVLN) framework built atop vision-language models (VLMs). SPF is capable of navigating to a…
3D FlowMatch Actor: Unified 3D Policy for Single- and Dual-Arm Manipulation
Nikolaos Gkanatsios, Jiahe Xu, Matthew Bronars +3
We present 3D FlowMatch Actor (3DFA), a 3D policy architecture for robot manipulation that combines flow matching for trajectory prediction with 3D pretrained visual scene represen…