Nonlinear filtering and control for an autonomous vehicle

A comprehensive analysis for the location problem of an autonomous mobile robot is presented. In order to decrease the frequency of the measurement and modeling errors correction, a method using an approximate nonlinear filtering technique was investigated. The performance of three filters has been analyzed for this problem of estimating vehicle position and heading using optical range measurement and odometry. The three filters yielded equal performances. However, for practical implementation reasons, the first-order filter was retained to extract the exact state of the mobile robot.<>