3 papers
cs.RO2025
Learning Long-Horizon Robot Manipulation Skills via Privileged Action
Xiaofeng Mao, Yucheng Xu, Zhaole Sun +3
Long-horizon contact-rich tasks are challenging to learn with reinforcement learning, due to ineffective exploration of high-dimensional state spaces with sparse rewards. The learn…
cs.RO2025
Dexterous Cable Manipulation: Taxonomy, Multi-Fingered Hand Design, and Long-Horizon Manipulation
Sun Zhaole, Xiao Gao, Xiaofeng Mao +3
Existing research that addressed cable manipulation relied on two-fingered grippers, which make it difficult to perform similar cable manipulation tasks that humans perform. Howeve…
cs.RO2024
DexSkills: Skill Segmentation Using Haptic Data for Learning Autonomous Long-Horizon Robotic Manipulation Tasks
Xiaofeng Mao, Gabriele Giudici, Claudio Coppola +4
Effective execution of long-horizon tasks with dexterous robotic hands remains a significant challenge in real-world problems. While learning from human demonstrations have shown e…