AIAA Guidance, Navigation, and Control Conference and Exhibit 2006
DOI: 10.2514/6.2006-6107
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On-Line Trajectory Planning for Aerial Vehicles: A Safe Approach with Guaranteed Task Completion

Abstract: On-line trajectory optimization in three dimensional space is the main topic of the paper at hand. The high-level framework augments on-line receding horizon control with an off-line computed terminal cost that captures the global characteristics of the environment, as well as any possible mission objectives. The first part of the paper is devoted to the single vehicle case while the second part considers the problem of simultaneous arrival of multiple aerial vehicles. The main contribution of the first part i… Show more

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Cited by 9 publications
(9 citation statements)
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“…When online control is carried, we take the state ( ) i k x t of system at each discrete moment i k t as the initial state, set up the length of planned horizon and seek the optimal control sequence k u of system in such planned horizon. Through acting the first item of control sequence k u to the system, we get new state of system and repeat executing the above operation by taking it as the initial condition, until the system state reaches the requirement of end constraint [6] [7] . Then, we map the schematic diagram to express the theory vividly.…”
Section: Algorithm Descriptionmentioning
confidence: 99%
“…When online control is carried, we take the state ( ) i k x t of system at each discrete moment i k t as the initial state, set up the length of planned horizon and seek the optimal control sequence k u of system in such planned horizon. Through acting the first item of control sequence k u to the system, we get new state of system and repeat executing the above operation by taking it as the initial condition, until the system state reaches the requirement of end constraint [6] [7] . Then, we map the schematic diagram to express the theory vividly.…”
Section: Algorithm Descriptionmentioning
confidence: 99%
“…It was found that planning in 3D could be conducted [17] to reduce the possibility of becoming trapped in local minima as the UA has the additional option of traversing over obstacles at a higher altitude. This section presents the formulation of loiter maneuvers for fixed wing aircraft using MA theory, and the application of safe state theory to trajectory planning in 3D partially known environments.…”
Section: Safe Trajectory Planningmentioning
confidence: 99%
“…UAS motion planning in 3D space has the advantage for allowing the execution of certain motion primitives (e.g. helical ascent) to escape local minima and continue operations [20]. In addition, during operations in dynamic and partially known environments, a greedy motion planning implementation can suffice as it may not be possible to find a global solution (e.g.…”
Section: Figure 3 -Greedy Search Algorithm Implementationmentioning
confidence: 99%