5 papers · 1 filter
DemoBot: Efficient Learning of Bimanual Manipulation with Dexterous Hands From Third-Person Human Videos
Yucheng Xu, Xiaofeng Mao, Elle Miller +4
This work presents DemoBot, a learning framework that enables a dual-arm, multi-finger robotic system to acquire complex manipulation skills from a single unannotated RGB-D video d…
Suction Leap-Hand: Suction Cups on a Multi-fingered Hand Enable Embodied Dexterity and In-Hand Teleoperation
Sun Zhaole, Xiaofeng Mao, Jihong Zhu +2
Dexterous in-hand manipulation remains a foundational challenge in robotics, with progress often constrained by the prevailing paradigm of imitating the human hand. This anthropomo…
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…
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…
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…