Journal of the ACM (JACM)
Vision for Mobile Robot Navigation: A Survey
IEEE Transactions on Pattern Analysis and Machine Intelligence
Robot Motion Planning
Planning Algorithms
Global Positioning Systems, Inertial Navigation, and Integration
Global Positioning Systems, Inertial Navigation, and Integration
Visual Navigation for Mobile Robots: A Survey
Journal of Intelligent and Robotic Systems
Introduction to Algorithms, Third Edition
Introduction to Algorithms, Third Edition
A Survey of Motion Planning Algorithms from the Perspective of Autonomous UAV Guidance
Journal of Intelligent and Robotic Systems
Vision-based unmanned aerial vehicle navigation using geo-referenced information
EURASIP Journal on Advances in Signal Processing - Special issue on signal processing advances in robots and autonomy
A Visual Global Positioning System for Unmanned Aerial Vehicles Used in Photogrammetric Applications
Journal of Intelligent and Robotic Systems
Three-dimensional Route Planning for Unmanned Aerial Vehicles in a Risk Environment
Journal of Intelligent and Robotic Systems
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In this paper we present an algorithm to determine a shortest trajectory of a fixed-wing UAV in scenarios with no-fly areas. The innovative feature is that not only the kinematic and dynamic properties, but also the navigational capabilities of the air vehicle are taken into account. We consider a UAV with landmark-based visual navigation, a technique which can cope with long-term GPS outages. A navigation update is obtained by matching onboard images of selected landmarks with internally stored geo-referenced images. To achieve regular updates, a set of landmarks must be identified which are passed by the air vehicle in a proper sequence and with appropriate overflight directions. The algorithm is based on a discretization of the airspace by a specific network. Each path in the network corresponds to a trajectory which avoids the no-fly areas and respects the flight performance of the air vehicle. Full functionality of the navigation can be ensured by dynamically adapting the network to the environmental conditions. A shortest trajectory is then obtained by the application of standard network algorithms.