Research On Path Planning Of Mobile Robot Based On Improved NSGA-? Algorithm

Multi-objective optimization problems exist in a wide range of scientific research and reallife applications.How to optimize each single objective in a multi-objective problem and finally obtain the optimal solution to meet the requirements is the key to study multi-objective optimization problems.In this paper,based on the study of the path planning problem of small mobile robots,static and dynamic motion scenarios with different degrees of complexity are established respectively,combined with an improved multi-objective genetic algorithm to study the path planning of mobile robots,and the optimization objectives involved in its path search process include path length,smoothness and safety.The NSGA-II algorithm with good robustness,fast convergence speed and high solution accuracy is chosen in this topic,and the algorithm is improved by proposing a ranking-based individual selection strategy,which is then applied to the study of robot path planning,aiming to search for a better motion trajectory between the starting and ending positions to meet the requirements.This paper first expounds the research background,significance and purpose of the topic,and analyzes and summarizes the research status of robot path planning.The general process of solving practical problems by multi-objective optimization is given,the research status of multi-objective optimization algorithm is analyzed,and the structure frame diagram of the paper is given.Then taking the small mobile robot as the research object,the kinematics analysis is made,and the corresponding kinematics model is established,and the realization principle of different motion modes is studied.Then the system composition of the mobile robot and the environmental information perception system are analyzed and summarized.Based on the odometer and laser radar sensor models,the relevant information processing principles obtained by the robot in the trajectory search process are analyzed,and the navigation technology of the mobile robot is analyzed from two aspects of navigation mode and positioning mode.Secondly,the principle of NSGA-II algorithm is expounded.On this basis,the NSGAII algorithm is improved,and the individual selection strategy based on sorting is proposed.The implementation steps of the improved algorithm are given,and the effectiveness of the improved strategy is analyzed.The path planning method of mobile robot is analyzed and studied,and the map model of robot motion environment is constructed.The corresponding fitness function is proposed and constructed according to the optimization goal in the path planning process.Finally,based on the simulation environment of MATLAB R2016 b,the simulation experiments are carried out in the environment scenarios with different obstacle distribution types,and the simulation results are compared with those of various algorithms,which verifies the improved algorithm in solving the path planning problem of mobile robots.In this paper,the rationality and superiority of the improved NSGA-II algorithm are verified through simulation experiments.Through the comparison of simulation experiments,it can be obtained that the path distance planned by the improved algorithm is shorter,and the smoothness is better.There is no obstacle on the feasible path from the starting point to the end point,and the convergence rate of the algorithm has also been significantly improved.Therefore,it can be proved that the improvement of the algorithm is effective and meets the path planning requirements of mobile robots.