基于遗传算法的机器人轨迹规划

D.C. Monteiro, M. K. Madrid
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引用次数: 8

摘要

使用遗传算法(GA)来规划称为Jeca III的机器人手臂的轨迹阶段。首先,将遗传算法应用于笛卡尔平面的避障轨迹规划,并给出了一些新的操作,如交叉。其次,利用经典遗传算法对关节空间进行了规划。这一阶段分为初始定位和增量定位两部分。初始定位的目的是将机械臂末端执行器定位在轨迹的第一个点,增量定位的目的是将末端执行器移动到轨迹的下一个点。结果是使用GAs完成了完整的轨迹规划,展示了这种人工智能技术的灵活性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Planning of robot trajectories with genetic algorithms
Uses genetic algorithms (GA) for planning the stages of the trajectory of a robot arm called Jeca III. First, the GAs are used for planning the trajectory in the cartesian plane with obstacle avoidance, and some new operations, like crossover, are shown. Second, planning in the joint spaces are implemented using the classical GA with some modifications. This stage is divided into two parts: initial positioning and incremental positioning. The initial positioning has the purpose of locating the end effector of the robot arm in the first point of the trajectory, and the incremental positioning of moving the end effector to the next point of the trajectory. The result is a complete trajectory planning with the GAs, demonstrating the flexibility of this technique of artificial intelligence.
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