ABSTRACT The Kalman Filter is traditionally viewed as a Prediction-Correction Filtering
Algorithm. In this report we show that it can be viewed as a Bayesian Fusion algorithm and …

Abstract The Kalman Filter is traditionally viewed as a prediction-correction filtering
algorithm. In this work we show that it can be viewed as a Bayesian fusion algorithm and …

One of the basic tasks for autonomous flight with aerial vehicles (drones) is the detection of
obstacles within its flight environment. As the technology develops and becomes more …

To learn the environment using multisensory information, we need both an accurate sensor
model and a reasonable sensor fusion methodology. Ultrasonic sensors provide good range …

This work proposes a novel filtering algorithm that constitutes an extension of Bayesian
particle filters to the Dempster–Shafer theory. Our proposal solves the multi-target problem …

Occupancy grid maps provide a reliable vehicle environmental model and usually process
data from range finding sensors. Object grid maps additionally contain information about the …

This work proposes a novel shape from silhouette (SfS) algorithm using the Dempster–
Shafer (DS) theory for dealing with inconsistent silhouettes. Standard SfS methods makes …

La fusion d'informations est apparue afin de gérer des quantités très importantes de
données multisources dans le domaine militaire [1, 141, 76, 77] et reste d'actualité dans ce …

Reliable vehicle environment perception is a basic prerequisite for advanced driver
assistant systems and autonomously driving cars. A common environment representation …

Keypoint matching is the task of accurately finding the location of a scene point in two
images. Many keypoint descriptors have been proposed in the literature aiming at providing …