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Path planning and control of soccer robot based on genetic algorithm

机译:基于遗传算法的足球机器人路径规划与控制

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Studying the optimization of the soccer robot path planning is significant because of the ever-changing situation of the arena. The system itself has non-linearity. The environment also has the characteristics of time varying, which requires the robot to cooperate with each other. Combining with the characteristics of a soccer robot system, this paper proposes a genetic algorithm for the path planning algorithm of a soccer robot, which enables the robot to find a relatively short path from the point to the target. In this paper, three common path-planning methods are introduced, and the advantages and disadvantages are compared. Then, a path planning method based onS-adaptive genetic algorithm is proposed. The main innovation point is to change the crossover probability and mutation probability in genetic operation. Therefore, that it can change the probability value autonomously with the change of genetic generation and individual in the group. This method can better save the effective individual, make the algorithm converges faster, and get the optimal individual under the same conditions. The path solved byS-adaptive algorithm realizes obstacle avoidance behavior in a short time, and the path is better than the traditional genetic algorithm.
机译:研究足球机器人路径规划的优化是显着的,因为竞技场的不断变化的情况。系统本身具有非线性。环境还具有时变的特点,这需要机器人彼此配合。本文组合了足球机器人系统的特点,提出了一种足球机器人路径规划算法的遗传算法,其使机器人能够从点到目标的点找到相对短的路径。在本文中,介绍了三种常见的路径规划方法,比较了优点和缺点。然后,提出了一种基于对自适应遗传算法的路径规划方法。主要创新点是改变遗传操作中的交叉概率和突变概率。因此,它可以随着组中的遗传生成和个人的变化而自主地改变概率值。此方法可以更好地保存有效个体,使算法收敛得更快,并在相同的条件下获得最佳个体。通过自适应算法解决的路径在短时间内实现了障碍避免行为,并且路径优于传统的遗传算法。

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