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Geometric In-Hand Regrasp Planning: Alternating Optimization of Finger Gaits and In-Grasp Manipulation

机译:几何式手部抓握计划:手指步态和抓握中的交替优化

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This paper explores the problem of autonomous, in-hand regrasping-the problem of moving from an initial grasp on an object to a desired grasp using the dexterity of a robot's fingers. We propose a planner for this problem which alternates between finger gaiting, and in-grasp manipulation. Finger gaiting enables the robot to move a single finger to a new contact location on the object, while the remaining fingers stably hold the object. In-grasp manipulation moves the object to a new pose relative to the robot's palm, while maintaining the contact locations between the hand and object. Given the object's geometry (as a mesh), the hand's kinematic structure, and the initial and desired grasps, we plan a sequence of finger gaits and object reposing actions to reach the desired grasp without dropping the object. We propose an optimization based approach and report in-hand regrasping plans for 5 objects over 5 in-hand regrasp goals each. The plans generated by our planner are collision free and guarantee kinematic feasibility.
机译:本文探讨了自动重新抓握的问题,即使用机器人手指的灵巧性将物体的最初抓握转移到所需抓握的问题。我们为这个问题提出了一个计划者,该计划者在手指步态和抓握操纵之间交替进行。手指步态使机器人可以将单个手指移动到对象上的新接触位置,而其余手指则可以稳定地握住对象。抓握操作可将对象移动到相对于机器人手掌的新姿势,同时保持手与对象之间的接触位置。给定对象的几何形状(作为网格),手的运动学结构以及初始的和所需的抓握,我们计划一系列手指步态和对象放置动作以达到所需的抓握而不会掉落对象。我们提出了一种基于优化的方法,并针对5个对象中的每个对象的5个手工重新绘制目标报告了手工重新绘制计划。我们的计划人员生成的计划是无冲突的,并保证了运动学上的可行性。

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