International Journal of Computer Vision
A Flexible New Technique for Camera Calibration
IEEE Transactions on Pattern Analysis and Machine Intelligence
Introductory Techniques for 3-D Computer Vision
Introductory Techniques for 3-D Computer Vision
Robust analysis of feature spaces: color image segmentation
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
An Inertial and Visual Sensing System for a Small Autonomous Helicopter
Journal of Robotic Systems
Control of a Quadrotor Helicopter Using Dual Camera Visual Feedback
International Journal of Robotics Research
WACV '07 Proceedings of the Eighth IEEE Workshop on Applications of Computer Vision
Computer Vision Onboard UAVs for Civilian Tasks
Journal of Intelligent and Robotic Systems
On-board and Ground Visual Pose Estimation Techniques for UAV Control
Journal of Intelligent and Robotic Systems
Survey of advances in guidance, navigation, and control of unmanned rotorcraft systems
Journal of Field Robotics
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In this paper we introduce a real-time trinocular system to control rotary wing Unmanned Aerial Vehicles based on the 3D information extracted by cameras located on the ground. The algorithm is based on key features onboard the UAV to estimate the vehicle's position and orientation. The algorithm is validated against onboard sensors and known 3D positions, showing that the proposed camera configuration robustly estimates the helicopter's position with an adequate resolution, improving the position estimation, especially the height estimation. The obtained results show that the proposed algorithm is suitable to complement or replace the GPS-based position estimation in situations where GPS information is unavailable or where its information is inaccurate, allowing the vehicle to develop tasks at low heights, such as autonomous landing, take-off, and positioning, using the extracted 3D information as a visual feedback to the flight controller.