Robotic Grasping of Common Objects: Focusing on Edge Detection for Improved Handling

Abstract

Grasping objects like plates and cups poses unique challenges for robots because of their irregular shapes and the difficulty of finding reliable grasp points.Traditional approaches often attempt to grasp the object at its center, but this strategy tends to fail for items like plates or cups, whose shapes deviate from simple forms like cubes or spheres.To address this issue, we propose a new method that utilizes AI-powered image analysis to identify the best edges for grasping.Through experiments conducted with a home service robot and a set of YCB objects, we evaluated the effectiveness of our approach compared to conventional methods.The results revealed a significant improvement in the success rate, particularly for objects with prominent edges, such as cups.