Application of Monte Carlo Localization Algorithm on Mobile Robot

In this paper, the method of mobile robot localization based on Monte Carlo algorithm (MCL) is proposed. The method is the probability distribution of mobile robot position in the moving environment is expressed using a series of particles with weights. The step of this algorithm is predicting particle position, followed by the calculation of particle weight, then updating the particle distribution, and finally estimating the robot position. The results show the localization effect based on Monte Carlo algorithm is better than Markov algorithm, and the localization precision can be improved by increasing the number of sensors and enhancing the frequency of sampling.