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Regrasping objects during manipulation tasks by combining genetic algorithms and finger gaiting

机译:通过结合遗传算法和手指步态在操作任务中对物体进行重新磨砂

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摘要

During a manipulation task with a mechanical hand, some particular situations occur frequently. For example, a finger can reach its joint limits or there can be a collision between two or more parts of the hand. In such situations, regrasping must be done without changing the position and the orientation of the object inside the hand. The objective is thus to insure the continuity of the manipulation task. In this work, we propose to compute a new feasible grasp by using genetic algorithms (GAs). The fourth finger enables to reach a new constraint-free grasp using finger gaiting. First we formulate the grasp synthesis problem as an optimization problem that we solve by using genetic algorithms. Once the new optimal grasp is found, a sequence of fingers motions involving the fourth finger is used to reach this new constraint-free grasp. These motions relocate successively the limiting fingers back to their workspace limits. The whole approach is detailed within this paper including the hand kinematics and motion planning. Simulations are shown in order to illustrate the efficiency of the proposed method with a mechanical hand designed in the ROBIOSS team of the PPRIME Institute.
机译:在用机械手进行操纵任务期间,经常会发生某些特殊情况。例如,手指可能达到其关节极限,或者手的两个或多个部分之间可能发生碰撞。在这种情况下,必须进行重新抓握而不改变手内部物体的位置和方向。因此,目的是确保操纵任务的连续性。在这项工作中,我们建议通过使用遗传算法(GA)计算一个新的可行把握。第四根手指能够通过手指步态达到新的无约束抓地力。首先,我们将抓握综合问题表述为通过使用遗传算法解决的优化问题。一旦找到新的最佳抓握,涉及第四根手指的一系列手指运动将用于达到这一新的无约束抓握。这些动作将限制手指依次重新定位到其工作空间限制。本文中详细介绍了整个方法,包括手运动学和运动计划。进行了仿真,以说明用PPRIME研究所的ROBIOSS团队设计的机械手提出的方法的效率。

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