摘要机器人路径规划是指在有障碍物的运动区域内，能够通过计算模拟出从起点出发到达指定目的地的各种可能，并选择出符合要求的最佳可能路线，使机器人在没有人为干预条件下安全无碰撞地避开所有障碍物，同时还需符合某一预设指标(如时间最短、转弯次数最少、耗能最低等)。

本文主要研究了现阶段路径规划算法的分类及优劣的评价，并对基于栅格法的蚁群路径优化进行了验证。本文将机器人的工作环境预先通过栅格法进行建模，来确定障碍的分布，模拟蚁群的觅食行为和食物特性，然后介绍了邻近区和食物气味区的概念，定义有效路径和无效路径的含义，然后在其他参数不变的情况下，分别改变蚁群数量 、启发因子 和信息素挥发系数 当中的某一参数，使用启发式信息素策略来搜索最优路径。对路径规划效果的影响进行了仿真检验分析，寻找出最佳整定参数。72855

该论文有图16幅，表6个，参考文献20篇。

毕业论文关键词: 蚁群算法  栅格法  路径规划

Study of Robot Path Planning

Abstract Robot path planning is refers to in has obstacles of movement regional within, can through calculation simulation out from beginning starting arrived specified destination of various may, and select out meet requirements of best may route, makes robot in no human intervention conditions Xia security no collision to avoid all obstacles, while also needed meet a preset index (as time shortest, and turn times at least, and energy minimum,)。 

This paper studies the current classification and quality evaluation of path planning algorithm and ant colony optimization based on grid method is verified。 This paper Will build the environment of work advance through gate grid method for robots to determine obstacles of distribution, simulation ant group of foraging behavior and food characteristics, and then introduce the area of near district and the concept of food smell district , defined effective path and invalid path of meaning, then in other parameter not variable of situation, respectively change ant group number , inspired factor , expects inspired factor and information pigment volatile coefficient among of a parameter, using heuristic information pigment strategy to search optimal path。 Path-planning simulation tests the effects of analysis, looking for optimal tuning parameters。 

The 16 charts, 6 tables, 20 references are presented in this paper。

Key Words:  ant colony optimization  grid method  path planning

目  录

摘  要 I

Abstract II

1 绪论 4

1。1 研究背景和意义 4

1。2 移动机器人的种类 4

1。3 机器人关键技术 4

1。4 本文章节结构安排 4

2 基本概念 4

2。1 导航与避障技术 4

2。2 移动机器人路径规划 4

2。3 本章小结 4

3 基于栅格法与蚁群算法的路径规划 4

3。1 栅格法 4

3。2 蚁群算法 4

3。3 本章小结 4

4 基于蚁群算法的仿真 4

4。1 基于蚁群算法最短路径仿真流程图 4

4。2 求解步骤