A Unified Multi-Task Deep Learning Framework for Robotic Bin-Picking of Planar Objects
An innovative approach is introduced for the random bin-picking of planar objects by developing a multi-task model for instance segmentation and keypoint detection in 2D images and a grasp candidate selection strategy is proposed to enable reliable grasping in cluttered industrial environments.