Path Planning Of Mobile Robot Based On Improved Wolf Pack Algorithm

With the development of modern science and technology and intelligence level,people devote themselves to the research of intelligent mobile robot.In this paper,an improved wolf swarm algorithm for mobile robot path planning is proposed,which is a new swarm intelligence optimization algorithm proposed in recent years.In order to expand and improve the theoretical system and practical application of the werewolf swarm algorithm,the algorithm has been improved.Further improve the local search ability of the wolf;construct the intelligent attack behavior,improve the ability of self-adaptive adjustment of the fierce wolf;put forward the centripetal circumference The attack strategy makes the algorithm converge to the global optimum.In order to verify the convergence of the algorithm,the Markov chain is used for positive code,and 15 standard test functions are used to test the performance of the algorithm.Particle swarm optimization,artificial bee swarm algorithm and artificial fish swarm algorithm are compared.The results show that the improved wolf swarm algorithm is more effective.Although the experimental results show that the performance of IWPA can be improved,the experimental results also contain strong randomness and error.Taguchi orthogonal test is introduced to further analyze the rules and parameters of the algorithm.Finally,the IWPA algorithm is applied to mobile robot path planning,algorithm parameters by using TAGUCHI orthogonal test and analysis of the objective function,in order to select experimental parameters,experimental comparison of IWPA algorithm and path planning based on WPA algorithm.The experimental results show that IWPA algorithm is better quality path planning,and improve the efficiency of mobile programming the robot path.