Task-Oriented Grasping Position Selection in Deformable Object Manipulation

Abstract

Grasping mechanisms in robotic deformable object manipulation (DOM) remain under-investigated due to the intrinsic complexity of DOM. For grasping in DOM, grasping position selection is crucial since external forces are applied to grasping locations on the deformable object (DO) to make it deform. The feasibility and efficiency of performing a specific DOM task thus highly depend on where grasps are placed. This letter investigates the grasping position selection problem in DOM. In particular, we tackle it in a task-oriented manner to facilitate robot deforming operations. For common deformation description methods (image feature and point cloud) and grasping scenarios (single and dual grasps), we develop grasping position selection methods that take into account the properties of both the task and DO. Specifically, metrics are first constructed to quantify grasping position quality when conducting the deforming process. Algorithms are then proposed based on metrics, which enable robots to select appropriate grasping positions in DOM. We evaluated our methods in both simulations and hardware experiments.