Omni-directional Vision Localization Based on Particle Filter
Zuoliang Cao, Shiyu Liu, Juha Röning · 2007
Omni-directional vision navigation appears definite significant since its advantage of panoramic sight with a single compact visual scene. This unique guidance technique involves target recognition, vision tracking, object positioning, path programming. An algorithm for omni-vision based global localization which utilizes two overhead features as beacon pattern is proposed in this paper. An approach for geometric restoration of omni-vision images has to be considered since an inherent distortion exists. The localization of the robot can be achieved by geometric computation. Dynamic localization employs a beacon tracker to follow the landmarks in real time during the arbitrary movement of the vehicle. Particle filter (PF) has been shown to be successful for several nonlinear estimation problems. A beacon tracker based on Particle filter which offers a probabilistic framework for dynamic state estimation in visual tracking has been developed. We have implemented the tracking and localization system and demonstrated the relevant of the algorithm.