[1]韦子文.基于改进蚁群算法的路径规划算法研究[J].高速铁路技术,2023,14(05):69-74.[doi:10.12098/j.issn.1674-8247.2023.05.013]
　WEI Ziwen.A Study on Path Planning Algorithm Based on Improved Ant Colony Algorithm[J].HIGH SPEED RAILWAY TECHNOLOGY,2023,14(05):69-74.[doi:10.12098/j.issn.1674-8247.2023.05.013]
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基于改进蚁群算法的路径规划算法研究()
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《高速铁路技术》[ISSN:1674-8247/CN:51-1730/U]

卷:
14卷
期数:
2023年05期
页码:
69-74
栏目:
出版日期:
2023-11-20

文章信息/Info

Title:
A Study on Path Planning Algorithm Based on Improved Ant Colony Algorithm
文章编号:
1674-8247(2023)05-0069-06
作者:
韦子文
中铁第一勘察设计院集团有限公司，? 西安 710043
Author(s):
WEI Ziwen
China Railway First Survey and Design Institute Group Co. ，Ltd. ，Xi’ an? 710043 ，China
关键词:
智能机器人; 路径规划; 多约束; 多邻域; 蚁群算法
Keywords:
intelligent robot; path planning; multi-constraint; multi-neighborhood; ant colony algorithm
分类号:
U284.92
DOI:
10.12098/j.issn.1674-8247.2023.05.013
文献标志码:
A
摘要:
智能机器人搬运铁路电务检修基地中待检修设备可极大提高日常运营维护的智能化水平。本文针对智能机器人在日常巡检过程中受到铁路电务检修基地室内通道及其自身实际运行工况等限制，提出了改进的蚁群算法以获取最优路径。首先，基于图论和二维栅格法对电务检修基地的室内布置进行环境建模。然后，通过分析智能机器人在实际工况下的各种约束，建立以路径最短、最平滑为目标的路径规划模型。接着，引入“分类学习”思想，增加蚁群蚁种，优化信息素更新策略，基于“节约里程法”思想在状态转移规则中引入距离节约因子，增加蚁群搜索方向等来改进传统蚁群算法。最后，通过实际案例进行仿真验证，本文算法与其他两种改进蚁群算法相比，路径距离更短、更平滑。
Abstract:
Intelligent robots can greatly improve the level of intelligence in daily operation and maintenance by transporting equipment to be repaired in railway communication and signaling maintenance depots. The paper addresses the limitations faced by intelligent robots during daily patrol due to indoor passages and their actual operating conditions at the railway communication and signaling maintenance depot. Firstly，a two-dimensional grid method based on graph theory was used to model the indoor layout of the maintenance depot，and a path planning model with the shortest and smoothest path as the goal was established by analyzing the various constraints faced by the intelligent robot in actual working conditions. Secondly，the traditional ant colony algorithm was improved by introducing the idea of “classification learning”，adding ant colony species，optimizing information update strategies，introducing distance-saving factors in the state transition rules based on the idea of “Saving Algorithm”，and increasing the direction of ant colony search，which was used to obtain the optimal path. Finally，simulation verification was carried out through practical cases，and compared with two other improved ant colony algorithms，this algorithm has a shorter and smoother path distance.

参考文献/References:

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备注/Memo

备注/Memo:
收稿日期：2022-06-15
作者简介：韦子文（1994-），男，工程师。
更新日期/Last Update: 2023-11-20