Comparison of robot localization methods using distributed and onboard laser range finders

In this paper we discuss methods for estimating the position of objects in environments that have both distributed sensing devices as well as mobile robots equipped with sensors - intelligent spaces. The aim is to use both types of devices for the estimation. We focus on the utilization of laser range finder devices as sensors, due to their good sensing characteristics. Our main interest here is in the localization of mobile robots and we consider two estimation methods. One is based on a heuristic determination of the center of the tracked object and utilizes a Kalman filter based estimation approach. The other method is based on geometric models of both the environment and the robot, and the position is estimated using a particle filter. The methods are described and experimental results are shown, and their comparison is given.