METHODS AND SYSTEM TO PREDICT HAND POSITIONS FOR MULTI-HAND GRASPS OF INDUSTRIAL OBJECTS

摘要

A computer-implemented method of predicting hand positions for multi-handed grasps of objects includes receiving a plurality of three-dimensional models and for each three-dimensional model, receiving user data comprising (i) user-provided grasping point pairs and (ii) labelling data indicating whether a particular grasping point pair is suitable or unsuitable for grasping. For each three-dimensional model, geometrical features related to object grasping are extracted based on the user data corresponding to the three-dimensional model. A machine learning model is trained to correlate the geometrical features with the labelling data associated with each corresponding grasping point pair and candidate grasping point pairs are determined for a new three-dimensional model. The machine learning model may then be used to select a subset of the plurality of candidate grasping point pairs as natural grasping points of the three-dimensional model.