US 12,377,549 B2
System and method for determining a grasping hand model
Francesc Moreno Noguer, Barcelona (ES); Guillem Alenyà Ribas, Barcelona (ES); Enric Corona Puyane, Barcelona (ES); Albert Pumarola Peris, Barcelona (ES); and Grégory Rogez, Meylan (FR)
Assigned to NAVER Corporation, Gyeonggi-do (KR)
Filed by Naver Corporation, Seongnam-si (KR); and Naver Labs Corporation, Seongnam-si (KR)
Filed on Jun. 6, 2022, as Appl. No. 17/833,460.
Application 17/833,460 is a continuation in part of application No. 17/341,970, filed on Jun. 8, 2021, abandoned.
Claims priority of provisional application 63/208,231, filed on Jun. 8, 2021.
Claims priority of application No. 202030553 (ES), filed on Jun. 9, 2020.
Prior Publication US 2022/0402125 A1, Dec. 22, 2022
Int. Cl. B25J 9/16 (2006.01)
CPC B25J 9/1697 (2013.01) [B25J 9/161 (2013.01)] 40 Claims
OG exemplary drawing
 
1. A system for determining parameters of a hand model suitable for grasping an object, comprising:
a first neural network for segmenting the object in an image;
a second neural network for predicting parameters of the hand model that define a pose for grasping the segmented object; and
a third neural network for refining the predicted parameters of the hand model to fit the segmented object by maximizing a number of contact points between the object in the image and the hand model while minimizing interpenetration;
wherein the refined predicted parameters of the hand model represent how a hand may grasp the object.