Robust dead reckoning is a complicated problem for wheeled mobile robots (WMRs), where the robots are faulty, such as the sticking of sensors or the slippage of wheels, for the discrete fault models and the continuous states have to be estimated simultaneously to reach a reliable fault diagnosis and accurate dead reckoning. Particle filters are one of the most promising approaches to handle hyb...

Knowing the uncertainty of measurements is important for sensor fusion using Kalman filters. Our sensor of interest is the Sick PLS101-112 laser range finder. We present an approach for straight line parameter estimation in polar coordinates that results in a simple covariance estimate and a worst case systematic line parameter error model based on a range error model backed up by experimental ...

In this paper we address the problem of assessing quantitatively the quality of traversability maps computed from data collected by an airborne laser range finder. Such data is used to plan paths for an unmanned ground vehicle (UGV) prior to the execution of long range traverses. Little attention has been devoted to the problem we address in this paper. We use a unique data set of geodetic cont...

In large-scale construction sites there are constant needs for rapid recognition and accurate measurement of objects so that on-site decisions can be made quickly and safely. Current methods involve full area laser range scanning systems that can produce very detailed models of a scanned scene, however the computational and data acquisition time that is required precludes the methods from being...

In this paper, we present a feature based approach for monocular scene reconstruction based on extended Kalman filters (EKF). Our method processes a sequence of images taken by a single camera mounted frontal on a mobile robot. Using different techniques, we are able to produce a precise reconstruction that is free from outliers and therefore can be used for reliable obstacle detection. In real...