A localization algorithm for low-cost cleaning robots based on kalman filter

Abstract

A novel localization algorithm with low-cost sensors for cleaning robots is presented in this paper, which includes fusing the data of encoders and an electronic compass to estimate the posture state of the robot by using Kalman filter. It judges the confidence of the data of the electronic compass with magnetic field intensity; judges the confidence of data of odometer by the information of slippage and collision. A coverage strategy and map construction methods with the localization algorithm are also introduced. Experimental results show that the proposed algorithm can achieve adequate localization precise enough for complete coverage and the cleaning robots have a superior coverage ratio with the coverage strategy.