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

机译:几何携带重新激发计划:交替优化手指Gaits和掌握操作

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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:本文探讨了自主,手中重新制作的问题 - 从对象上的初始抓握到所需掌握的问题,使用机器人的手指的灵活性。我们为这个问题提出了一个规划师,在手指Gaiting和掌握操作之间交替。手指踏板使机器人能够将单手指移动到物体上的新接触位置,而剩余的手指稳定地保持该物体。掌握操作将物体相对于机器人的手掌移动到新的姿势,同时保持手和物体之间的接触位置。鉴于对象的几何形状(作为网格),手的运动结构和初始和期望的掌握,我们计划一系列手指Gaits和物体重构动作,以达到所需的掌握而不滴下对象。我们提出了一种基于优化的方法,并报告了5个对象的手法重新制作计划,每次超过5个对象。我们的计划者产生的计划是免费的,保证运动可行性。

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