Path Planning of Mobile Robot Based on Improved Genetic Algorithm

Abstract

Abstract With the continuous development of science and technology, mobile robots are gradually applied to people’s routine life. As one of the key technologies of mobile robots, the performance of path planning algorithms is a significant factor affecting its efficiency. On the basis of using a traditional Genetic Algorithm for path planning, combined with specific application scenarios, this paper proposes a new path planning algorithm for mobile robots. The path smoothness and the number of path corners are added to the fitness function to evaluate the path, so as to select a more superior path. Simulation experiments in MATLAB show the validity and feasibility of the modified method. By comparison to the traditional GA and other classical path planning algorithms, the optimal path selected has fewer turning angles under the same path length, which has a better application effect and greatly improves the working efficiency and stability.