Dynamic Omnidirectional Vision Localization Using a Beacon Tracker Based on Particle Filter

Abstract

We establish omni-directional vision system with fisheye lens and solve the problem of fisheye image distortion. A method for calibrating the omni-vision system is proposed to generate the center of a fisheye lens image. A novel fisheye image rectification algorithm based on SVM, which is different from the conventional method is introduced. Beacon recognition and tracking are key procedures for an omni-vision guided mobile unit. A Particle Filter (PF) has been shown to be successful for several nonlinear estimation problems. A beacon tracker based on a Particle Filter which offers a probabilistic framework for dynamic state estimation in visual tracking has been developed. Dynamic localization employs a beacon tracker to follow landmarks in real time during the arbitrary movement of the vehicle. The coordinate transformation is devised for path programming based on time sequence images analysis. Conventional image processing such as shape decomposition, description, matching, and other usually employed techniques are not directly applicable in omni-vision. We have implemented the tracking and localization system and demonstrated the relevance of the algorithm. The significance of the proposed research is the evaluation of a new calibration method, global navigation device and a dynamic omni-directional vision navigation control module using a beacon tracker which is based on a particle filter through a probabilistic algorithm on statistical robotics. An on-board omni-vision navigator based on a compatible DSP configuration is powerful for autonomous vehicle guidance applications.