Unmanned aerial vehicle flight path planning based on adaptive ant colony optimization algorithm
Ting Zhang · Computer Integrated Manufacturing Systems · 2012
To solve the problem of Unmanned Aerial Vehicle(UAV)route planning,Adaptive Ant Colony Optimization(AACO)algorithm was proposed.Different from the global search mode of standard Ant Colony Optimizatio(ACO),local search mode was adopted by AACO.Based on the relative position of starting node and destination node,one of the appropriate search mode in four was selected,and transition probabilities of each candidate node were calculated.The next node was selected according to the roulette principle.The simulation result showed that AACO algorithm had advantages such as few search nodes,quick speed and so on.It could reduce flight path cost and computing time.In addition,AACO could also avoided singular flight path segment,thus the attained practical flight path could fly was guaranteed.Therefore,the performance of AACO was much better than standard ACO.