Introduction to Autonomous Mobile Robots
Introduction to Autonomous Mobile Robots
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
Monocular Vision for Mobile Robot Localization and Autonomous Navigation
International Journal of Computer Vision
Parametric correspondence and chamfer matching: two new techniques for image matching
IJCAI'77 Proceedings of the 5th international joint conference on Artificial intelligence - Volume 2
Journal of Field Robotics - Visual Mapping and Navigation Outdoors
International Journal of Computer Vision
Impact of Landmark Parametrization on Monocular EKF-SLAM with Points and Lines
International Journal of Computer Vision
Appearance-Guided Monocular Omnidirectional Visual Odometry for Outdoor Ground Vehicles
IEEE Transactions on Robotics
Parametric ego-motion estimation for vehicle surround analysis using an omnidirectional camera
Machine Vision and Applications
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In recent years, classical structure from motion based SLAM has achieved significant results. Omnidirectional camera-based motion estimation has become interested researchers due to the lager field of view. This paper proposes a method to estimate the 2D motion of a vehicle and mapping by using EKF based on edge matching and one point RANSAC. Edge matching based azimuth rotation estimation is used as pseudo prior information for EKF predicting state vector. In order to reduce requirement parameters for motion estimation and reconstruction, the vehicle moves under nonholonomic constraints car-like structured motion model assumption. The experiments were carried out using an electric vehicle with an omnidirectional camera mounted on the roof. In order to evaluate the motion estimation, the vehicle positions were compared with GPS information and superimposed onto aerial images collected by Google map API. The experimental results showed that the method based on EKF without using prior rotation information given error is about 1.9 times larger than our proposed method.