Vision-Based 6-DoF Grasp Pose Estimation for Robot Cloth Unfolding
This work proposes center direction regression network (CeDiRNet)-6DoF, a deep learning framework that jointly predicts effective grasp points and the complete 6-DoF grasp pose from the observed cloth configuration by integrating dense 3-D grasp regression with segmentation and sine-cosine-encoded Euler angles.