EARL: Eye-on-Hand Reinforcement Learner for Dynamic Grasping with Active Pose Estimation
Baichuan Huang,Jingjin Yu,Siddarth Jain,Baichuan Huang,Jingjin Yu,Siddarth Jain
In this paper, we explore the dynamic grasping of moving objects through active pose tracking and reinforcement learning for hand-eye coordination systems. Most existing vision-based robotic grasping methods implicitly assume target objects are stationary or moving predictably. Performing grasping of unpredictably moving objects presents a unique set of challenges. For example, a pre-computed robu...
