Semantic and stability-aware grasp pose estimation for unseen objects using deformable shape models

In this study, we propose a semantic grasping method that accounts for post-grasp stability without requiring a preexisting 3D shape of the object. Among multiple candidate grasp points, the method selects the one that minimizes the moment at the grasp point with respect to the object’s centroid. This paper proposes a semantic grasping method that explicitly considers post-grasp stability without requiring an instance-specific 3D shape model. The method estimates a grasp pose that minimizes moment at the grasp point with respect to the object’s centroid, thereby maintaining a stable orientation after lifting. In experiments, we evaluated post-grasp stability against conventional methods; the proposed method maintained a stable state in 18 out of 25 trials, outperforming the conventional method (4 out of 25).