A Computational Approach to Edge Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Invariant Descriptors for 3D Object Recognition and Pose
IEEE Transactions on Pattern Analysis and Machine Intelligence - Special issue on interpretation of 3-D scenes—part I
3D interpretation of conics and orthogonality
CVGIP: Image Understanding
Three-dimensional computer vision: a geometric viewpoint
Three-dimensional computer vision: a geometric viewpoint
Direct Least Square Fitting of Ellipses
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Flexible New Technique for Camera Calibration
IEEE Transactions on Pattern Analysis and Machine Intelligence
Research on computer vision-based for UAV autonomous landing on a ship
Pattern Recognition Letters
A Vision-Based Guidance System for UAV Navigation and Safe Landing using Natural Landmarks
Journal of Intelligent and Robotic Systems
Low-Cost Visual Tracking of a Landing Place and Hovering Flight Control with a Microcontroller
Journal of Intelligent and Robotic Systems
Automatic Take Off, Tracking and Landing of a Miniature UAV on a Moving Carrier Vehicle
Journal of Intelligent and Robotic Systems
Vision Based Position Control for MAVs Using One Single Circular Landmark
Journal of Intelligent and Robotic Systems
Trajectory generation and control for precise aggressive maneuvers with quadrotors
International Journal of Robotics Research
A Run-Based Two-Scan Labeling Algorithm
IEEE Transactions on Image Processing
A Cross-Platform Comparison of Visual Marker Based Approaches for Autonomous Flight of Quadrocopters
Journal of Intelligent and Robotic Systems
On-Board Dual-Stereo-Vision for the Navigation of an Autonomous MAV
Journal of Intelligent and Robotic Systems
Autonomous Landing of MAVs on an Arbitrarily Textured Landing Site Using Onboard Monocular Vision
Journal of Intelligent and Robotic Systems
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In this paper, we present an onboard monocular vision system for autonomous takeoff, hovering and landing of a Micro Aerial Vehicle (MAV). Since pose information with metric scale is critical for autonomous flight of a MAV, we present a novel solution to six degrees of freedom (DOF) pose estimation. It is based on a single image of a typical landing pad which consists of the letter "H" surrounded by a circle. A vision algorithm for robust and real-time landing pad recognition is implemented. Then the 5 DOF pose is estimated from the elliptic projection of the circle by using projective geometry. The remaining geometric ambiguity is resolved by incorporating the gravity vector estimated by the inertial measurement unit (IMU). The last degree of freedom pose, yaw angle of the MAV, is estimated from the ellipse fitted from the letter "H". The efficiency of the presented vision system is demonstrated comprehensively by comparing it to ground truth data provided by a tracking system and by using its pose estimates as control inputs to autonomous flights of a quadrotor.