In a recent article [1] we surveyed the state-of-the-art in Unscented techniques for nonlinear estimation, and we provided a number of examples that illustrate its advantages over traditional linearized approaches such as the Extended Kalman Filter (EFK). Unfortunately, the description of the reentry example in Section VI.B of the paper was not completely and correctly explained and was not ent...

In normal working conditions it is possible to achieve sufficient attitude estimation accuracy for a satellite using regular Kalman filter algorithm. On the other hand, when there is a fault in the measurements, the Kalman filter fails in providing the required accuracy and may even collapse over time. In this paper, a Robust Kalman filtering method is proposed for the attitude estimation probl...

Intuitively representing the motion of a snake robot is difficult. This is in part because the internal shape changes that the robot uses to locomote involve the entire body and no single point on the robot intuitively represents the robot’s pose at all times. To address this issue, we present a method of defining body coordinate frames that departs from the typical convention of rigidly fixing...

Zusammenfassung: Diese Arbeit beschreibt einen Ansatz zur Lokalisierung von Mobilrobotern mittels der Kombination eines Laserscanners mit monokularem Video. Das Verfahren ist merkmalsbasiert und benutzt ein erweitertes Kalman filter (EKF) zur Datenfusion und Positionsschätzung. Die Umgebungsmerkmale sind Liniensegmente für den Laserscanner und vertikale Kanten für die Kamera. Physikalisch gut b...

An algorithm for real-time estimation of the pose of a moving object of known geometry is considered. The algorithm is based on a discrete-time Extended Kalman Filter which computes the object pose on the basis of visual measurements of the object features. The robustness of the algorithm with respect to measurement noise and modelling errors is improved by considering a full adaptive version o...

This paper suggests a new approach to the problem of harmonic signal estimation. The idea is to model the harmonic signal as a function of the state of a second order nonlinear ordinary differential equation (ODE). The function of the right hand side of the nonlinear ODE is parameterized with a polynomial model. A Kalman filter and an extended Kalman filter are then developed. The proposed meth...

In this study, we consider a special situation that only a pair of hydrophone on a moving underwater vehicle is available to localize a fixed acoustic source of far distance. The trigonometry can be used in this situation by using two different DOA of different locations. Notice that the distance between the two locations should be measured. Therefore, we assume that the vehicle is sailing stra...

We consider the localization problem for a unicycle robot equipped with range finders and moving in environments with nonsmooth geometry, i.e., whose obstacle-free region has a piecewise-linear boundary. Using the Multi-Hypothesis Density Filter, a novel multi-modal estimator based on the bayesian framework, an innovative localization system is devised and implemented on the ATRV-Jr robot. Expe...

Two main difficulties in process monitoring are lack of reliable measurements of key process variables and difficulty in defining quantitative relationships between state variables. In this study sensor networks are used to demonstrate an approach based on Kalman filtering to model the specific monitoring systems. Kalman filtering at both local nodes and fusion center are the covariance matrice...

The use of the extended Kalman filter (EKF) is heavily eneenched in non-linear signal procesging applications. However linearisatioa erron inhenmt in the s p e c i f i i n of an EKF can severely degrade its performance. This paper presents a new approach to the robus-tification of the EKF by application of the robust linear design methods b d o n t h e € L wr"inimisationcritexion. Theresults of...