Research of the Path Planning of Mobile Robot based on Improved Ant Colony Algorithm

Yu Yong

doi:10.16578/j.issn.1004.2539.2016.07.012

您当前的位置：

首页 >

文章列表页 >

Research of the Path Planning of Mobile Robot based on Improved Ant Colony Algorithm

更新时间：2022-10-20

- Research of the Path Planning of Mobile Robot based on Improved Ant Colony Algorithm
- Vol. 40, Issue 7, Pages: 58-61(2016)
- 作者机构：
  
  1. 河南经贸职业学院信息管理系
- 作者简介：
- 基金信息：
- DOI：10.16578/j.issn.1004.2539.2016.07.012
  CLC：
扫描看全文
[1]余勇.基于改进蚁群算法的移动机器人路径规划研究[J].机械传动,2016,40(07):58-61.

Yu Yong. Research of the Path Planning of Mobile Robot based on Improved Ant Colony Algorithm. [J]. 40(7):58-61(2016)
[1]余勇.基于改进蚁群算法的移动机器人路径规划研究[J].机械传动,2016,40(07):58-61. DOI： 10.16578/j.issn.1004.2539.2016.07.012.

Yu Yong. Research of the Path Planning of Mobile Robot based on Improved Ant Colony Algorithm. [J]. 40(7):58-61(2016) DOI： 10.16578/j.issn.1004.2539.2016.07.012.

摘要

传统的蚁群算法在移动机器人路径规划过程中,在加速算法收敛时易陷入局部最优问题,针对此问题提出了一种新型蚁群算法的移动机器人路径规划方法。首先建立了机器人路径规划数学模型,在此基础上对传统的蚁群算法进行了改进,将环境中局部的机器人路径信息引入到蚁群信息素的初始化和路径选择概率中,提高了蚁群算法的收敛速度并防止算法早熟。通过引入交叉操作并对蚁群算法中参数进行调整,避免了算法陷入局部最优。仿真结果表明,所提方法能够明显提高最佳路径搜索能力,整体性能优于传统蚁群算法。

Abstract

The traditional ant colony algorithm in the process of mobile robot path planning,the algorithm is easy to fall into the local optimization problem when the convergence of the algorithm. Aiming at this problem,a new ant colony optimization for mobile robot path planning method is proposed. Firstly,the mathematical model of the robot path planning is established. Based on this,the traditional ant colony algorithm is improved,and the local robot path information is introduced into the initialization of ant colony pheromone and the probability of path selection,which improves the convergence speed of ant colony algorithm and prevents premature. By introducing the crossover operation and adjusting the parameters of the ant colony algorithm,the algorithm can avoid local optimization. The simulation results show that the proposed method can significantly improve the optimal path search capability,the overall performance is better than the traditional ant colony algorithm.

关键词

移动机器人路径规划新型蚁群算法数学模型收敛速度局部最优

Keywords

Mobile robot path planningNew ant colony algorithmMathematical modelConvergence speedLocal optimum

references

Views

326

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

Analysis of the Influence of the Parameters of the Pendulum Mechanism of the Swashplate Engine on the Dynamic Performance

Influence of Assembly Errors and Tooth Surface Modification on Transmission Errors of Curvilinear Cylindrical Gears

A Forming Method and Theoretical Verification of Curvilinear Cylindrical Gears for Adjustable Contact Area

Design and Analysis of Electromechanical Controlled Globoidal Cam System

General Mathematical Model of the Intersecting Cross-axis Gear based on Conjugate Curve

Related Author

No data

Related Institution

School of Mechantronics & Vehicle Engineering, Chongqing Jiaotong University

The Green Aerotechnics Research Institute of Chongqing Jiaotong University

Chongqing Key Laboratory of Green Aviation Energy and Power

School of Aeronautics, Chongqing Jiaotong University

School of Intelligent Manufacturing, Panzhihua University

⁰