Determination of the Attitude of 3D Objects from a Single Perspective View
IEEE Transactions on Pattern Analysis and Machine Intelligence
Determination of Camera Location from 2-D to 3-D Line and Point Correspondences
IEEE Transactions on Pattern Analysis and Machine Intelligence
Moment preserving detection of elliptical shapes in gray-scale images
Pattern Recognition Letters
Multiple view geometry in computer vision
Multiple view geometry in computer vision
Linear Pose Estimation from Points or Lines
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
Detection of Concentric Circles for Camera Calibration
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1 - Volume 01
Single view based pose estimation from circle or parallel lines
Pattern Recognition Letters
Single view metrology from scene constraints
Image and Vision Computing
Image moments: a general and useful set of features for visual servoing
IEEE Transactions on Robotics
Journal of Intelligent and Robotic Systems
Journal of Intelligent and Robotic Systems
Modeling and Adaptive Tracking Control of a Quadrotor UAV
International Journal of Intelligent Mechatronics and Robotics
Adaptive Nonlinear Stabilization Control for a Quadrotor UAV: Theory, Simulation and Experimentation
Journal of Intelligent and Robotic Systems
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This paper presents a real-time vision based algorithm for 5 degrees-of-freedom pose estimation and set-point control for a Micro Aerial Vehicle (MAV). The camera is mounted on-board a quadrotor helicopter. Camera pose estimation is based on the appearance of two concentric circles which are used as landmark. We show that that by using a calibrated camera, conic sections, and the assumption that yaw is controlled independently, it is possible to determine the six degrees-of-freedom pose of the MAV. First we show how to detect the landmark in the image frame. Then we present a geometric approach for camera pose estimation from the elliptic appearance of a circle in perspective projection. Using this information we are able to determine the pose of the vehicle. Finally, given a set point in the image frame we are able to control the quadrotor such that the feature appears in the respective target position. The performance of the proposed method is presented through experimental results.