Towards visual navigation in dynamic and unknown environment: trajectory learning and following, with detection and tracking of moving objects.

The global objective of these works concerns the navigation of autonomous robots on long routes in outdoor dynamic environments, more precisely on the development and the evaluation of advanced perception functions, embedded on vehicles moving in a convoy formation, on an a priori unknown route in urban or natural environments. Three issues are tackled: first several methods from the State of the Art have been integrated in order to cope with the visual mapping and the trajectory learning problems for a vehicle A equipped with a stereovision sensor, moving in a large-scale environment, assumed static. Then it is proposed two modes for the execution of this trajectory by a vehicle B equipped by a single camera: either a delayed mode, in which B loads initially all representations learnt by A, and executes alone the recorded trajectory, or a convoy mode, in which B follows A, which sends him by a communication link, the trajectory sections as soon as they are learnt. Finally, it has been considered changing and dynamic environments, dealing with the detection of events from images acquired on a dynamic vehicle: detection of changes (disappearances or appearances of static objects, typically cars parked in a urban environment), or detection of mobile objects (pedestrians or other vehicles). Résumé