Gross motion planning—a survey
ACM Computing Surveys (CSUR)
Network flows: theory, algorithms, and applications
Network flows: theory, algorithms, and applications
Approximation schemes for the restricted shortest path problem
Mathematics of Operations Research
Communications of the ACM
Robot Motion Planning
Motion Planning in Dynamic Environments
Motion Planning in Dynamic Environments
Computers and Intractability; A Guide to the Theory of NP-Completeness
Computers and Intractability; A Guide to the Theory of NP-Completeness
Cruise Missile Mission Planning: A Heuristic Algorithm for Automatic Path Generation
Journal of Heuristics
Computing the shortest path: A search meets graph theory
SODA '05 Proceedings of the sixteenth annual ACM-SIAM symposium on Discrete algorithms
Planning Algorithms
Geospatial Analysis: A Comprehensive Guide to Principles, Techniques and Software Tools
Geospatial Analysis: A Comprehensive Guide to Principles, Techniques and Software Tools
Engineering Route Planning Algorithms
Algorithmics of Large and Complex Networks
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
Path Planning Strategies for UAVS in 3D Environments
Journal of Intelligent and Robotic Systems
A simple efficient approximation scheme for the restricted shortest path problem
Operations Research Letters
Performance evaluation of constraint-based path selection algorithms
IEEE Network: The Magazine of Global Internetworking
Flight path planning for unmanned aerial vehicles with landmark-based visual navigation
Robotics and Autonomous Systems
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This paper introduces a new approach for three-dimensional flight path optimization for unmanned aerial vehicles. It considers the performance of the air vehicle as well as mission specific requirements including the avoidance of no-fly areas, risk reduction in threat environments by terrain following flight or terrain masking low-level flight, and other regulations such as fixed release and approach vectors at the start and destination locations. The focus of the approach is on a proper discretization of the airspace by a network which allows the application of standard algorithms of combinatorial optimization. In contrast to conventional discretizations by grids or grid-like graphs, our network is non-regular since created by some random process. Moreover, each path in the network corresponds to a twice continuously differentiable trajectory which obeys the kinematic restrictions of the air vehicle and which is feasible with respect to the operational requirements of the mission. With suitable costs defined on the edges of the network, a minimum-cost path calculation allows to identify a trajectory of shortest length, shortest flight time, minimum flight height, or minimum visibility from the ground. The latter objectives aim to minimize the probability of being detected by hostile forces, hence increasing the survivability of the air vehicle.