Monte Carlo Self-localization Based on Characteristic Particles

摘要

An approach for multi-robot self-localization based on Monte Carlo method is described.In the approach,grid cells are used to describe the whole particles space that is used in MCL(Monte Carlo Localization) method to estimate the pose of robot,then variable grid cells are used to extract the characteristic particles that can represent the whole property of the particles on estimating the robot pose.Because the number of characteristic particles is greatly less than the number of whole particles,the problem of overabundant dimensionalities caused by directly using MCL in collaborative localization of multi-robot can be solved.This approach can reduce the complexity of computation while keeping the precision of estimation.The simulation results show that it can get good collaborative localization performance in multi-robot system.