基于遗传算法的协作机器人最优路径规划与力矩最小化

D. Garg, Manish Kumar
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引用次数: 4

摘要

本文提出了一种基于遗传算法的多机器人构型最优轨迹确定策略及其应用。首先,简要介绍了多机器人控制的动机和协作机器人领域的研究现状。接下来是对机器人背景下的能量最小化技术的讨论,最后,包括使用遗传算法作为优化工具的原理。指定了末端执行器的初始位置和最终位置。两种情况,一种是单个机械手,另一种是两个协作机械手携带共同有效载荷,说明了所提出的方法。遗传算法基于最小关节力矩要求识别最优轨迹。适当定义的涉及关节扭矩的性能指标的最小化意味着由此获得的轨迹需要最少的扭矩。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Optimal Path Planning and Torque Minimization via Genetic Algorithm Applied to Cooperating Robotic Manipulators
This paper presents the formulation and application of a genetic algorithm based strategy for the determination of an optimal trajectory for a multiple robotic configuration. First, the motivation for multiple robot control and the current state-of-art in the field of cooperating robots are briefly given. This is followed by a discussion of energy minimization techniques in the context of robotics, and finally, the principles of using genetic algorithms as an optimization tool are included. The initial and final position of the end effector are specified. Two cases, one of a single manipulator, and the other of two cooperating manipulators carrying a common payload illustrate the approach proposed. The genetic algorithm identifies the optimal trajectory based on minimum joint torque requirements. The minimization of a suitably defined performance index involving joint torques implies that the trajectory thus obtained requires the least amount of torque.
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