Robot path planning with improved variable-step ant colony algorithm in unknown environment

XU Yuqiong; LOU Ke; LI Zhikun

doi:10.13873/J.1000-9787(2021)09-0150-03

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Robot path planning with improved variable-step ant colony algorithm in unknown environment

更新时间：2025-09-11

- Robot path planning with improved variable-step ant colony algorithm in unknown environment
- Issue 9, Pages: 150-152+156(2021)
- 作者机构：
  
  1. 广州大学松田学院电气与汽车工程学院
  2. 高端装备先进感知与智能控制教育部重点实验室
  3. 安徽工程大学安徽省电气传动与控制重点实验室
- 作者简介：
- 基金信息：
- DOI：10.13873/J.1000-9787(2021)09-0150-03
  CLC： TP18;TP242
- Published：2021
- 稿件说明：
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XU Yuqiong, LOU Ke, LI Zhikun. Robot path planning with improved variable-step ant colony algorithm in unknown environment[J]. 2021, (9): 150-152+156.
DOI：

XU Yuqiong, LOU Ke, LI Zhikun. Robot path planning with improved variable-step ant colony algorithm in unknown environment[J]. 2021, (9): 150-152+156. DOI： 10.13873/J.1000-9787(2021)09-0150-03.

摘要

针对蚁群算法在移动机器人进行路径规划时存在路径较长、收敛速度较慢等问题

提出改进变步长蚁群算法。改进平滑度机制

对移动机器人产生的多次转角进行平滑处理;引入平滑度引导函数

诱导移动机器人爬行节点朝向最优路径;改进蚁群系统

对不同路径进行比较

加强最优路径信息素浓度;引入信息素惩罚函数

避免移动机器人陷入死锁或局部最优。仿真实验结果表明:改进变步长蚁群算法相较于其它算法大幅度提高移动机器人搜索效率

验证了该算法的优越性。

Abstract

Aiming at the problems of long path and slow convergence speed when ant colony algorithm is used in path planning of mobile robot

an improved variable-step ant colony algorithm is proposed.The algorithm improves the smoothness mechanism

smoothes the multiple corners generated by the mobile robot

introduces the smoothness guidance function

induces the mobile robot to crawl the node toward the optimal path

improves the ant colony system

compares different paths

and strengthens pheromone concentration of the optimal path introduces pheromone penalty function to prevent the mobile robot from falling into a deadlock or local optimum.Simulation experiment results show that the improved variable-step ant colony algorithm greatly improves the search efficiency of mobile robots compared with other algorithms

which verifies the superiority of the algorithm.

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