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.

中文翻译：

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规划人形机器人的抓取动作

本文解决了获得人形机器人所需的运动以执行试图模仿人类协调的手-臂运动的抓握动作的问题。第一步是数据采集和分析，包括在抓握几个日常物体（包括四种可能的抓握类型）的同时捕捉人类运动，将它们映射到机器人并计算预抓握和抓握阶段的手部运动协同作用（每掌握型）。然后，完成抓取和运动合成步骤，其中包括使用四种家庭类型为给定对象生成潜在的抓取，并使用基于双向多目标采样的规划器来规划运动，从而有效地指导运动规划在缩小的搜索空间中遵循协同作用，从而产生具有人类外观的路径。