2026-04-17T04:29:10Zhttps://recercat.cat/oai/request

oai:recercat.cat:2117/1778942026-01-14T08:18:45Zcom_2072_1033col_2072_452950

00925njm 22002777a 4500 dc Rosell Gratacòs, Jan author Suárez Feijóo, Raúl author García, Néstor author Ud Din, Muhayy author 2019-12-15 This paper addresses the problem of obtaining the required motions for a humanoid robot to perform grasp actions trying to mimic the coordinated hand–arm movements humans do. The first step is the data acquisition and analysis, which consists in capturing human movements while grasping several everyday objects (covering four possible grasp types), mapping them to the robot and computing the hand motion synergies for the pre-grasp and grasp phases (per grasp type). Then, the grasp and motion synthesis step is done, which consists in generating potential grasps for a given object using the four family types, and planning the motions using a bi-directional multi-goal sampling-based planner, which efficiently guides the motion planning following the synergies in a reduced search space, resulting in paths with human-like appearance. The approach has been tested in simulation, thoroughly compared with other state-of-the-art planning algorithms obtaining better results, and also implemented in a real robot. Peer Reviewed Postprint (author's final draft) Àrees temàtiques de la UPC::Informàtica::Robòtica Autonomous robots Robots -- Motion Motion planning Grasp planning Human-like appearance Robots autònoms Robots -- Moviment Planning grasping motions for humanoid robots