基于混沌蜂群算法的农用无人直升机路径规划

Path Planning for Agricultural Unmanned Helicopter Based on Chaos Artificial Bee Colony Algorithm

针对农用无人直升机从地面站飞到目标农田的路径规划问题,提出了一种改进的人工蜂群算法。在该算法中利用混沌局部搜索算子的遍历性和随机性的特点重新初始化陷入局部最优解的雇佣蜂,在迭代中产生局部最优解的邻域点,帮助其脱离束缚并快速找到全局最优解。采用改进算法来处理无人直升机的路径规划任务,首先将路径规划任务通过数学建模转换成一个多维函数优化问题,然后结合人工蜂群算法的全局寻优能力和混沌算子的局部搜索能力得到改进算法,最后分别用仿真实验验证了改进算法在函数优化上的优越性和在解决农用无人直升机路径规划上的可行性。

Aiming at the problem of the planning for unmanned helicopter from ground station to target farm,an advanced artificial bee colony optimization algorithm is presented. In this algorithm,due to the ergodicity and irregularity of the chaotic,it is to initialize the employed bees which are fallen into the local optimum solutions. It can produce some neighbourhood points of the local optimum solutions in an iteration to help employed bees flee the bound and find the global optimum solutions. Dealing with the path planning for unmanned helicopter,firstly,the task of unmanned helicopter path planning was transformed into a multi-dimensional optimization problem through mathematical model. Then the improved algorithm made use of the chaotic search to improve the capability of precise search and also kept the ability of global search of artificial bee colony algorithm. Lastly,the functions optimization problems and the path planning task were tested through the proposed algorithm. The experimental results show that the improved algorithm is feasible and superior in solving path planning of agricultural unmanned helicopter.