Research On Robot Path Planning Based On Artificial Fish Genetic Algorithm

Robot path planning is one of the most important research directions in robot technology.Along with the domestic and foreign scholars research on path planning method increasing,it makes the application range of robots increasingly wide,and it has great influence on people's life,the development of society and the innovation of science and technology.Path planning is that the robot can find a path according to the task requirements,and the path need to meet the requirement to connect the starting point and the end,but also to bypass all obstacles.The main contents of this paper are as follows:1.The significance,development trend and current research situation of mobile robot path planning are understood,and the traditional path planning method and intelligent path planning method are studied and analyzed.2.The basic genetic algorithm is studied,and its advantages and disadvantages are analyzed.Aiming at the problem of low precision and slow convergence of genetic algorithm due to the effect of initial population quality,a discontinuous and barrier-free method is proposed to generate initial population.A new design of genetic manipulation is also carried out.The improved genetic algorithm is applied to path planning to verify its effectiveness.3.Learn the theoretical knowledge and optimization steps of artificial fish swarm algorithm,and analyze its advantages and disadvantages.In order to solve the problem that artificial fish swarm algorithm is easy to get into local optimum due to the behavior selection,a new behavior selection strategy is proposed and the foraging behavior is improved.The improved artificial fish swarm algorithm is applied to robot path planning,good effect.4.By analyzing the advantages and disadvantages of artificial fish swarm algorithm and genetic algorithm,a path planning method combining artificial fish swarm algorithm and genetic algorithm is proposed.The main idea is to select the nodes through the clustering,rear-end and foraging behavior of artificial fish in the grid environment,and to realize the path search.The searched path is regarded as the initial group of genetic algorithm.Through genetic algorithm to achieve the solution of the optimal path;finally through the simulation,the three algorithms are compared to verify the feasibility and superiority of artificial fish swarm genetic algorithm.