Research On Path Planning Of Wave Glider Based On Genetic-improved Ant Colony Fusion Algorithm

The wave glider is a kind of unmanned autonomous vehicle used for observation of the marine environment.Its unique two-body mechanism can convert wave fluctuations into driving force,and it has the characteristics of ultra-long endurance,autonomous navigation and positioning,and artificial intelligence recognition.The wave glider can carry various sensors according to the mission requirements to carry out data acquisition of the marine environment,and realize the communications relay and target monitoring in the sea surface,underwater and air.The new type of monitoring platform overcomes the energy limitation of traditional ocean observation methods and makes long-distance and long-term ocean observation possible.Our country has achieved independent research of the wave glider and mastered key technologies such as communication,navigation,and monitoring.Path planning is a prerequisite of autonomous navigation,and it's also the major difficulties of research work.Based on the research and analysis of the path planning algorithm,and the dynamic characteristics and navigation environment of the wave glider,the ant colony algorithm based on artificial pathfinder ants(ACA-Apa)is proposed in this paper.First of all,the artificial pathfinder ant is introduced to explore the distribution of obstacles in the direction of feasible nodes in advance,and feed back the information to the search ants,so as to increase the visual range of the search ants,and keep ants getting trapped inside the obstacles to turn back or die,and reduce the possibility of the algorithm falling into deadlock;secondly,the influences of the marine environment on the speed of the wave glider are considered comprehensively,the comprehensive effect of route distance and time-consuming is improved;finally,the mutation operator is introduced,and the direction of variation is controled by the number of path nodes and the concentration of pheromone.This ways increase the diversity of solutions,and improve the convergence rate of the algorithm at the same time.In order to further improve the performance of the algorithm,the ACA-Apa algorithm and the improved genetic algorithm are fused to improve the iterative convergence speed of the algorithm.For the dynamic obstacle environment,the idea of quadratic planning is adopted,that is,first of all,the path planning is carried out in static obstacle environment,then the dynamic local path planning is carried out in dynamic obstacle environment,and last,some local paths are smoothed to reduce the impact of partial paths which be changed due to avoiding obstacles on the overall path effect.The experimental results show that the fusion algorithm can be applied to different marineenvironments,and avoids effectively the algorithm deadlock and local optimal solution,and improves the convergence speed,the planned route distance is short and the security is high.