三维环境中机器人路径规划方法研究

Research on path planning method of robot in 3D environment

针对三维未知环境中的机器人路径规划问题研究,提出一种基于改进人工蜂群算法的路径规划方法。首先,在传统人工蜂群算法中引入正态分布思想优化蜜源初始化分布,提高初始化的目的性,为后续搜索提供精度保证。其次,优化迭代过程中蜜源位置更新方式,构建蜜源中心领域范围内搜索新蜜源的数学模型。采用MATLAB软件曲面网格划分,构建三维未知环境模型。然后,通过MATLAB软件仿真,将改进人工蜂群算法与传统人工蜂群算法和蚁群算法相比较,发现改进人工蜂群算法程序运行时间更短、陷入局部最优次数更少,求解精度更高,并验证了本文提出方法的可行性。

Aiming at the research of robot path planning in 3D unknown environment,a path planning method based on improved artificial bee colony algorithm is proposed.Firstly,the idea of normal distribution is introduced into the traditional artificial bee colony algorithm to optimize the initial distribution of nectar sources,improve the purpose of initialization,and provide precision guarantees for subsequent searches.Secondly,the update method of the nectar source location in the iterative process is optimized,and a mathematical model for finding new nectar sources in the central area of the nectar source is established.MATLAB software is used to divide the surface mesh,so as to build a three-dimensional unknown environment model.Then,through MATLAB software simulation,the improved artificial bee colony algorithm is compared with the traditional artificial bee colony algorithm and ant colony algorithm.It is found that improved artificial bee colony algorithm has the features of shorter program running time,fewer traps in local optimum,and higher solution precision,which verifies the feasibility of the proposed method.