Human-Robot Collaborative Tele-Grasping in Clutter With Five-Fingered Robotic Hands

Abstract

Teleoperation offers the possibility of enabling robots to replace humans in operating within hazardous environments. While it provides greater adaptability to unstructured settings than full autonomy, it also imposes significant burdens on human operators, leading to operational errors. To address this challenge, shared control, a key aspect of human-robot collaboration methods, has emerged as a promising alternative. By integrating direct teleoperation with autonomous control, shared control ensures both efficiency and stability. In this letter, we introduce a shared control framework for human-robot collaborative tele-grasping in clutter with five-fingered robotic hands. During teleoperation, the operator's intent to reach the target object is detected in real-time. Upon successful detection, continuous and smooth grasping plans are generated, allowing the robot to seamlessly take over control and achieve natural, collision-free grasping. We validate the proposed framework through fundamental component analysis and experiments on real-world platforms, demonstrating the superior performance of this framework in reducing operator workload and enabling effective grasping in clutter.