Representing and Tracking of Dynamics Objects using Oriented Bounding Box and Extended Kalman Filter.

Representing and tracking of dynamics objects is one of the main parts of autonomous navigation in urban areas. In the framework of the development of a multiple objects tracking system using multisensor fusion, this paper presents an oriented bounding box (OBB) representation with uncertainty computation as well as a model for object tracking. The uncertainty computation method, which takes into account Laser Range Finder sensor uncertainty and object's relative position, is evaluated. The influence of this uncertainty on the accuracy of the estimation is shown. The tracking model, based on the Extended Kalman Filter is tested and evaluated using the OBB object's representation.