Research On Path Planning Of Mobile Robot Based On Improved Genetic Algorithm

With the rapid development of computer network, automation, artificial intelligence and other technologies, the research of mobile robot technology has entered a new stage. Path planning is an important task in the research of mobile robot technology, and it is also the necessary foundation for the mobile robot to accomplish other tasks. Through in-depth study on the path planning technology, the mobile robot can be better used in the military, medical, service, entertainment, and other aspects to really blend in people’s daily life, and promote the progress of human society and the development of science and technology.In this paper, we mainly study the path planning of mobile robot based on genetic algorithm and other related problems. Based on the basic genetic algorithm,the path planning method of the improved genetic algorithm is studied in the paper,which improves the searching probability of the algorithm and the convergence speed of the algorithm.According to the characteristics of path planning, this paper designs the mobile robot path planning method based on genetic algorithm at first, in which including other designs about the environment modeling, the chromosome coding, path evaluation, genetic operators. The crossover and mutation operation of the basic genetic algorithm is random operation. Although the crossover and mutation of traditional genetic algorithm are randomization and simple, they can produce infeasible path in path planning, increase amount of computation, have the impact of the convergence speed. Genetic manipulation based on traditional genetic algorithm is improved by using prior knowledge to guarantee the feasibility of the path aftergenetic manipulation, at the same time this paper presents a new adaptive mode to improve the search efficiency of the algorithm optimization. At last, as it is easy for genetic algorithm to fall into the optimal local, the accept determination is proposed by using the metropolis based on simulated annealing algorithm. By comparing the improved genetic algorithm with other genetic algorithm, the result shows that the improved genetic algorithm has better convergence speed and optimization capabilities. By using the MATLAB to analysis and compare the results of the improved algorithm, which verify the improved genetic algorithm have made relatively good effect both in the speed of convergence, optimization effect, and searching ability in the field of mobile robot path planning.Finally, we use the Creative Star modular robot to build a mobile platform and apply the improved genetic algorithm to guide the mobile robot to carry out the static path planning. The results is satisfactory at last.