2006
DOI: 10.2514/1.25400
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Two-Point Flight Path Planning Using A Fast Graph-Search Algorithm

Abstract: This paper presents a method, using a fast graph-search algorithm, of finding a feasible flight path for an air vehicle that flies between two locations. This flight path must satisfy the many constraints required to make the flight safe and efficient. We start by constructing a virtual terrain as a search space above the real terrain, to take into account real flight conditions and the limitations of the vehicle's performance. Consideration of safe altitude, the horizontal safety distance of the flight path a… Show more

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Cited by 5 publications
(10 citation statements)
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“…The artificial potential field method was proposed in [31][32][33] for navigating mobile robots. The artificial potential field method is considered a bridge connecting obstacle avoidance and route searching problem.…”
Section: B Artificial Potential Field Methodsmentioning
confidence: 99%
“…The artificial potential field method was proposed in [31][32][33] for navigating mobile robots. The artificial potential field method is considered a bridge connecting obstacle avoidance and route searching problem.…”
Section: B Artificial Potential Field Methodsmentioning
confidence: 99%
“…UAV path planning using Particle Swarm Optimization and digital pheromones incorporating vehicle mechanics to generate multiple 3-d paths for operators have been proposed [24], as have optimization algorithms for multiobjective drone route planning [32]. Fast graph search algorithms that satisfy constraints on flights have been used to determine the optimum path of a drone traveling between two given locations [13] and UAV flight path planning in time-space varying wind fields using a kinematic tree path planner have been developed [12]. None of these techniques have sought to pre-build the flight paths of drones and then allow them to navigate along the path.…”
Section: Related Workmentioning
confidence: 99%
“…One important part of the navigation and guidance systems proposed in this work is the FPPS. In this paper, the FPPS is designed by using the A-Star (A*) algorithm [ 3 ] which is a best-first graph search algorithm to plan the flight path, and the system is able to reduce the computation load and improve the efficiency [ 4 ]. Moreover, the FPPS developed in this work is capable of generating a flight path that excludes any predefined forbidden zone.…”
Section: Introductionmentioning
confidence: 99%
“…In 2006, the Remotely Piloted Vehicle and Microsatellite Research Laboratory (RMRL) at the Institute of Aeronautics and Astronautics (IAA) of National Cheng Kung University (NCKU) built a path planning system using a fast graph-search algorithm to find a feasible flight path for an UAV to traverse multiple targets [ 4 ]. Based on the real flight conditions and the limitations of the UAV’s performance, the system constructed a virtual terrain as a search space above the real terrain.…”
Section: Introductionmentioning
confidence: 99%
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