基于改进蚁群算法的果园移动机器人路径规划研究

Research on Path Planning of Orchard Mobile Robot Based on Improved Ant Colony Algorithm

蚁群算法作为一种模仿蚂蚁觅食行为的仿生算法,常常被人们优先用于路径规划。但是,普通蚁群算法计算量大,容易出现局部最优化。为了提高最短路径搜索速度,建立了新的基于方向夹角的启发因子,使得蚂蚁优先选择夹角小的节点作为下一移动节点;同时采用了较复杂的对角线距离的倒数作为新的启发式因子,该距离公式无需进行平方根运算,求解简单,再一次提高了搜索效率。实验表明:在同等最短路径的情况下,与原蚁群算法相比,最短路径的搜索效率提升了3倍。满足在复杂果园环境下移动机器人的实时路径规划需求。

Ant colony algorithm,as a Bionic algorithm that mimics the foraging behavior of ants,is often used as a priority for path planning.However,the general ant colony algorithm has a large amount of calculation and is prone to local optimization.In order to improve the search speed of the shortest path,a new heuristic factor based on direction angle was established,which made the ant choose the node with small angle as the next moving node.At the same time,the reciprocal of the more complex diagonal distance was used as a new heuristic factor.The distance formula was not needed to perform square root operation,the solution was simple,and the search efficiency was improved again.The experiment shows that the search efficiency of the shortest path is three times higher than that of the original ant colony algorithm,under conditions of same shortest paths.Meet the real-time path planning requirement of mobile robot in complex orchard environment.