In this paper, the extended Kalman filtering (EKF) technique is considered for 3-dimensional tracking of vehicle movement using a fixed camera that provides vehicle images showing several marks, easily detectable, fixed to the vehicle body. The algorithm will be implemented in a minihelicopter hover-stabilization application. For this problem, we present results on the convergence and the domai...

This paper presents new algorithms to implement simultaneous localisation and map building (SLAM) in environments with very large number of features. The algorithms present an efficient solution to the full update required by the Compressed Extended Kalman Filter algorithm (CEKF). It makes uses of the Relative Landmark Representation (RLR) to develop very close to optimal de-correlation solutio...

This paper addresses the problem of visual-inertial navigation when processing camera observations of both point and line features detected within a Manhattan world. First, we prove that the observations of: (i) a single point, and (ii) a single line of known direction perpendicular to gravity (e.g., a non-vertical structural line of a building), provide sufficient information for rendering all...

We aimed to record and visualize the investigation activities of search and rescue dogs. The dog’s trajectory is required to create this visualization, and the dog’s velocity needs to be determined to estimate its trajectory. In this study, we examined a method for velocity estimation that uses a dog’s gait. We measured a Labrador dog’s gaits (walk and trot) and analyzed the gait data. From the...

We describe a model-based object tracking system that updates the configuration parameters of an object model based upon information gathered from a sequence of monocular images. Realistic object and imaging models are used to determine the expected visibility of object features, and to determine the expected appearance of all visible features. We formulate the tracking problem as one of parame...

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...