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Novel approach for robot path planning based on numerical artificial potential field and genetic algorithm

机译:基于数值人工势场和遗传算法的机器人路径规划新方法

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摘要

A novel approach for collision-free path planning of a multiple degree-of-freedom (DOF) articulated robot in a complex environment is proposed. Firstly, based on visual neighbor point (VNP), a numerical artificial potential field is constructed in Cartesian space, which provides the heuristic information, effective distance to the goal and the motion direction for the motion of the robot joints. Secondly, a genetic algorithm, combined with the heuristic rules, is used in joint space to determine a series of contiguous configurations piecewise from initial configuration until the goal configuration is attained. A simulation shows that the method can not only handle issues on path planning of the articulated robots in environment with complex obstacles, but also improve the efficiency and quality of path planning.
机译:提出了一种在复杂环境下多自由度(DOF)多关节机器人的无碰撞路径规划的新方法。首先,基于视觉邻点(VNP),在笛卡尔空间中构造了一个数值人工势场,该场为机器人关节的运动提供了启发信息,到目标的有效距离以及运动方向。其次,在联合空间中使用遗传算法结合启发式规则,以确定从初始配置到达到目标配置的一系列连续配置。仿真表明,该方法不仅可以解决复杂障碍环境下多关节机器人的路径规划问题,而且可以提高路径规划的效率和质量。

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