Research for an algorithm of UAV three-dimensional path planning
Ye Chun, Zhang Xi-huang · DOAJ (DOAJ: Directory of Open Access Journals) · 2018
Aiming at the basic artificial bee colony algorithm in the optimization process of the three-dimensional path planning for the unmanned aerial vehicles, the algorithm can be trapped in local optimum. And the rate of convergence or efficiency of the path planning would be reduced at the last stage. To overcome above problem, an improved ABC algorithm has been proposed in this paper. Firstly, with the model of planning space consisting of longitude, latitude and altitude information and terrain established, the cost value of the path planning has been obtained. Then, an adaptive search strategy is introduced to increase the speed of convergence. A new probability of selection strategy is introduced to keep the diversity of the population. And a chaotic sequence with Logistic map is adopted to iporove its robustness. Finally, the effectiveness of the improved algorithm has been verified through the three-dimensional path planning simulation and the local newly planning for the emergent threats. All the results show that the proposed algorithm has improved the global optimizing ability, and has a great advantage of convergence property and robustness compared with the genetic algorithm or traditional ABC algorithm. And the proposed algorithm is fit for solving path planning.