Research On Infrared Localization Method Of Micro-mobile Robot Based On Particle Filtering

In recent years,with the development of technologies related to Micro Electro Mechanical System,the highly integrated information processing and control circuits have laid the foundation for the research and application of micro robots.The localization problem is the basis for autonomous operation of micro robots.In this paper,based on the infrared localization model,the particle filter algorithm is used to study the self-positioning problem of micro mobile robots in a known environment.The main work is as follows:1.According to the structural characteristics of micro robots,an infrared selfpositioning model of micro robots is designed,and on this basis,a relative positioning model of micro robots is designed.The simulation and error analysis of the infrared relative location model verified the usability of this model for the relative positioning of micro robots.In practical applications,the position-determined robots can be used as landmarks,using relative position information to locate the positioning robot.2.Several Bayesian filtering algorithms,including Kalman filtering,extended Kalman filtering and particle filtering algorithms,are outlined and simulated.Simulation experiments verify the superiority of particle filter algorithm for state estimation.3.The particle filter algorithm is applied to the state estimation problem of mobile micro robots.The particle set of the robot pose information at each time is updated with the sensor information.The particle set is used to approximate the robot's current pose state.Among them,the odometer information is used to update the pose information of the particles,and the infrared sensor information is used to update the weight of each particle.The feasibility of the particle filter localization algorithm was verified by positioning simulation experiments.