Research on dynamic path planning of mobile robot based on genetic algorithm

WANG Hai-ying1; CAI Xiang-dong1; YOU Bo1; ZHANG Li-yong2

doi:10.13873/j.1000-97872007.08.014

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Research on dynamic path planning of mobile robot based on genetic algorithm

更新时间：2025-09-11

- Research on dynamic path planning of mobile robot based on genetic algorithm
- Issue 8, Pages: 32-34(2007)
- 作者机构：
  
  1. 哈尔滨理工大学自动化学院
  2. 哈尔滨理工大学测控技术与通信工程学院
- 作者简介：
- 基金信息：
- DOI：10.13873/j.1000-97872007.08.014
  CLC： TP18;TP242
- Published：2007
- 稿件说明：
移动端阅览
[1]王海英,蔡向东,尤波,张礼勇.基于遗传算法的移动机器人动态路径规划研究[J].传感器与微系统,2007(08):32-34.

WANG Hai-ying1, CAI Xiang-dong1, YOU Bo1, et al. Research on dynamic path planning of mobile robot based on genetic algorithm[J]. 2007, (8): 32-34.
[1]王海英,蔡向东,尤波,张礼勇.基于遗传算法的移动机器人动态路径规划研究[J].传感器与微系统,2007(08):32-34. DOI： 10.13873/j.1000-97872007.08.014.

WANG Hai-ying1, CAI Xiang-dong1, YOU Bo1, et al. Research on dynamic path planning of mobile robot based on genetic algorithm[J]. 2007, (8): 32-34. DOI： 10.13873/j.1000-97872007.08.014.

摘要

针对移动机器人未知、动态环境下路径规划的难题

对移动机器人进行了系统设计

采用动态栅格法对环境建模

在对传统遗传算法进行一定的改进的基础上

个体评价函数采取可行路径适应度函数和不可行路径适应度函数分别进行处理

通过算法设计和仿真可知

采用该方法对移动机器人进行动态路径规划时

与任何障碍物不发生碰撞

路径短而且规划曲线平滑

达到了满意的规划效果和收敛速度。

Abstract

Aimed at the unknown and dynamic environment path planning problem of the mobile robot

mobile robot system is designed

dynamic grid is used to make environmental modeling

on the basis of the traditional genetic algorithm definite improvement

individual evaluation function may take feasible path fitness function and not feasible path fitness function separately.The algorithm design and simulation indicate that the method is used to the dynamic path planning of mobile robot

not with any barrier collision

path short and planning curve smoothing

satisfactory results and planning convergence rate are achieved.

关键词

Keywords

references

基于遗传算法的移动机器人的一种路径规划方法 [J]. 王强,姚进,王进戈. 哈尔滨工业大学学报 . 2004(07)

基于遗传算法的多移动机器人协调路径规划 [J]. 孙树栋,林茂. 自动化学报 . 2000(05)

Industrial Robot Navigation and Obstacle Avoidance Employing Fuzzy Logic [J] . P. G. Zavlangas,S. G. Tzafestas. Journal of Intelligent and Robotic Systems . 2000 (1)

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