Quasi Monte Carlo localization for mobile robots

Abstract

In this paper, the authors will present a novel approach called Quasi Monte Carlo localization (QMCL) to address the problem of the inefficient uniform random sequence generated by the Monte Carlo method and hence the unnecessary large sample set used for initialization of Monte Carlo localization. With an additional new motion model, the performance of QMCL is even improved. The efficiency of the QMCL is evaluated by both simulation and experimental tests.