A navigation system based on an omnidirectional vision sensor

In this paper we present a dynamic localization system, allowing a mobile robot to evolve autonomously in a structured environment. Our system is based on the use of two sensors : an odometer and an omnidirectional vision sq,stem which gives a reference in connection with a set of natural beacons. Our navigation algorithm gives a reliable position estimation thanks to a systematic dynamic resetting. To merge our data, we use the Extended Kalman Filter (EKF). Our proposed method allows us to treat efficiently the noise problems linked to the primitive extraction, which contributes to the robustness olf our system. Thus, we get a reliable and quick navigation system which can answer the constraints of security and real time linked to the moving of the robots in an industrial environment. We give the experimental results obtained from a mission realized in an a priori known environment.