IMPLEMENTATION OF A KALMAN FILTER IN POSITIONING FOR AUTONOMOUS VEHICLES, AND ITS SENSITIVITY TO THE PROCESS PARAMETERS

Modern autonomous vehicles are using more than one method for performi ng the positioning task. The most common positioning methods for indoo r vehicles are odometry for relative positioning and triangulation for absolute positioning. In many cases a Kalman filter is required to me rge the data from the positioning systems and determines the vehicle p osition based on error analysis of the measurements and calculation pr ocedures. A Kalman filter is particularly advantageous for ''on-the-fl y'' positioning, which is performed while the vehicle is ita motion. T his paper presents the implementation of a Kalman filter in ''ROBI'' - an AGV for material handling in a manufacturing environment. The perf ormance of the filter in estimating the position of the AGV and the ef fect of motion parameters (speed, path curvature, beacon layout etc.) on filter accuracy are shown.