4 papers · 1 filter
Learning Object-Centric Motion Priors from Human for Robotic Dexterous Manipulation
Zhengdong Hong, Guofeng Zhang
Manipulating diverse objects with multi-fingered dexterous hands is challenging due to the high dimensionality and complex dynamics. Human-Object Interaction (HOI) datasets provide…
SyncHeC: Markerless Spatio-Temporal Hand-Eye Calibration via Differentiable Rendering and Continuous-Time Joint Optimization
Zhengdong Hong
Markerless hand-eye calibration under continuous motion requires jointly resolving camera geometry and the time offset between images and joint states. We present SyncHeC (Synchron…
Learning Adaptive Dexterous Grasping from Single Demonstrations
Liangzhi Shi, Yulin Liu, Lingqi Zeng +3
How can robots learn dexterous grasping skills efficiently and apply them adaptively based on user instructions? This work tackles two key challenges: efficient skill acquisition f…
EasyHeC++: Fully Automatic Hand-Eye Calibration with Pretrained Image Models
Zhengdong Hong, Kangfu Zheng, Linghao Chen
Hand-eye calibration plays a fundamental role in robotics by directly influencing the efficiency of critical operations such as manipulation and grasping. In this work, we present…