Real-Time Grasping Planning for Robotic Bin-Picking and Kitting Applications

Abstract

Multi-fingered robotic hands can potentially offer a higher degree of dexterity for grasping a variety of parts than a traditional parallel gripper or a custom end of arm tool. However, real-time grasp planning for complex robotic hands is a challenging task. In this paper, we present real-time grasping planning algorithms that utilize two simple yet effective dimension reduction strategies. The first strategy is the “intersected volume” computation which places the robotic palm relative to the object as well as its environment. The second strategy is the “finger curling planes” which decomposes a grasp contact computation problem in high-dimensional configuration space into several independent grasp contact computation problems in low-dimensional configuration space. Our algorithms have been demonstrated with simulation, physical experiments, and robotic bin-picking and kitting applications on two robotic platforms with three different robotic hands.