Robot SLAM algorithm based on laser range finder for large scale environment

Abstract

A simultaneous localization and mapping(SLAM) algorithm based on Rao-Blackwellised particle filter was presented for autonomous robot in large scale environment.Through selecting the stable and distinctive landmarks,a new data association method was proposed based on global constraints,accordingly the probability of error matching was decreased much.Then,an improved proposal function was adopted to improve the performance of particle filter.Experimental results showed that the algorithm has low computational complexity and high precision,and it can solve the robot SLAM problem in large scale environment.