| Nowadays,with the rapid development of science and technology,all walks of life are gradually using artificial intelligence technology,and there are many mature algorithms for the research of intelligent technology.In this paper,based on the traditional ant colony algorithm,the optimization is carried out to improve the optimization performance of the algorithm,and the corresponding solution is proposed for the path planning of unmanned craft.The traditional ant colony algorithm is based on the research of ant colony foraging behavior.The algorithm logic is a bionic stochastic algorithm based on ants’ collaborative foraging task,which is used to solve the problem of search and optimization.Core elements are the ant colony algorithm to search the information released by the individual element,through the pheromone to traverse a path,path traversal,the more pheromone concentration is higher,the ant colony when choosing the path have very good guide effect,this process is ant colony algorithm is feedback phenomenon,is also a unique algorithm.Based on the research on the positive feedback mechanism of ant colony algorithm,this paper finds the shortcomings of the algorithm.In order to make up for the shortcomings of the algorithm,it optimises the positive feedback mechanism and adds the negative feedback mechanism to improve the algorithm.Firstly,it is necessary to master the basic principle,mathematical model and logic flow of analyzing ant colony algorithm,then determine the influence of parameters on the performance of the algorithm,and finally improve the overall algorithm.Part for improving the increase of negative feedback mechanism is also inspired by group biological behavior,this improved method has the advantage of using only the most optimal path in the original algorithm on the basis of increased use of worst path,so that we can reduce the ant in the process of experiment of poor path to explore,improve the unknown path choice probability.It not only improves the overall performance of the algorithm,but also provides more possibilities for the final result.In the improved content,the negative feedback pheromone and the negative feedback pheromone update mode are added on the basis of the traditional ant colony algorithm’s path selection probability formula and pheromone update mode.To experimental process is rigorous,first by grid method to modeling of environment,and then to the traditional algorithm for testing,to determine the feasible range of the parameters,the improved algorithm experiment,at the same time to determine whether the improved algorithm has the feasibility,finally in order to more intuitive show the superiority of the improved algorithm will be improved algorithm and the traditional ant colony algorithm in different environment model were analyzed.The main purpose of this paper is to bring the ant colony algorithm with improved negative feedback mechanism into the research of unmanned craft path planning,compare and analyze the optimized performance of the improved algorithm under different complexity environment models,and judge whether it has the ability to solve path optimization.Through MATLAB experiment and comparison of simulation results,the stability and reliability of the improved algorithm have been improved,which can be put into the practical application of unmanned boat path planning. |
