一种动态参数更新的无人机三维路径规划方法  

A Kind of UAV Three-dimensional Path Planning Method by Dynamic Parameter Update

作　　者：张华[1] 史思总 周一廷 霍建文[1] 

机构地区：[1]西南科技大学信息工程学院,四川绵阳621010

出　　处：《自动化仪表》2015年第9期17-21,共5页Process Automation Instrumentation

基　　金：四川省科技厅科技支撑计划基金资助项目(编号:2014RZ0049)

摘　　要：针对动态环境下无人机三维路径规划的复杂性及优化效率问题,提出了一种可视域下动态参数更新的无人机三维路径规划方法。在动态参数更新过程中,采用启发式动态更新机制的信息素进行全局更新;利用模拟栅格法进行两次空间区域划分,形成局部节点集合和全局离散点集合。先在节点集合中搜索局部路径,然后在离散点集合中搜索出最优路径。为更好地逼近真实环境,算法引入函数DF1产生复杂的三维动态环境。实验结果表明,新的蚁群算法具有较好的可行性和实时性,能够有效解决空间复杂度、搜索效率等问题,加快全局收敛速度,保持基本蚁群算法较强的鲁棒性,实时避开障碍物规划出最优路径。Aiming at the complexity and optimize efficiency problems of three-dimensional path planning of UAV（ unmanned aerial vehicle） in dynamic environment, an ant colony algorithm by dynamic parameters update under a visual domain is proposed. Dynamic parameter update process of the ant algorithm, using heuristic dynamic update mechanism updates global pheromone and using the simulation grid method to zone the space twice and form the local node-set and global collection of discrete points. The algorithm searches partial path between the nodes, and then search for the optimal path between the discrete points. To better approximate real-world environment, the algorithm introduced dynamic function 1 （ DF1 ） produce complex three-dimensional dynamic environment. Through experimental results, the proposed algorithm has good feasibility and real-time for avoiding obstacle and planning the optimal path in real-time, and it can effectively solve spatial complexity, the search efficiency, and accelerate the global convergence speed at the same time maintaining the strong robustness of basic ant colony algorithm.

关 键 词：无人机 三维路径规划 蚁群算法 可视域 动态参数更新 

分 类 号：TP24[自动化与计算机技术—检测技术与自动化装置]