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Erschienen in: Intelligent Service Robotics 3/2017

21.03.2017 | Original Research Paper

Optimal 3D trajectory generation in delivering missions under urban constraints for a flying robot

verfasst von: Abolfazl Lavaei, M. A. Amiri Atashgah

Erschienen in: Intelligent Service Robotics | Ausgabe 3/2017

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Abstract

Interest in applying flying robots especially quadcopters for civil applications, in particular for delivering purposes, has dramatically grown in the recent years. In fact, since quadcopters are capable of vertical takeoff and landing, they can be widely employed for nearly any aerial task where a human presence is hazardous or response time is critical. In this regard, quadcopters come to be very beneficial in delivering packages; accordingly, generating an optimal flight trajectory plays a preponderant role for meeting this vision. This paper is concerned with generation of a time-optimal 3D path for a quadcopter under municipal restrictions in delivering tasks. To this end, the flying robot’s dynamics is first modeled through Newton–Euler method. Subsequently, the problem is formulated as a time-optimal control problem such that the urban constraints, which are safe-margins of high-rise buildings located throughout the course, are first modeled and then imposed to the trajectory optimization problem as inequality constraints. After discretizing the trajectory by means of Hermit–Simpson method, the optimal control problem is transformed into a nonlinear programming problem and finally is solved by the direct collocation technique. Extensive simulations demonstrate the efficacy of the proposed method and correspondingly verify the effectiveness of the suggested method in generation of optimum 3D routes while all constraints and mission requirements are satisfied.

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Metadaten
Titel
Optimal 3D trajectory generation in delivering missions under urban constraints for a flying robot
verfasst von
Abolfazl Lavaei
M. A. Amiri Atashgah
Publikationsdatum
21.03.2017
Verlag
Springer Berlin Heidelberg
Erschienen in
Intelligent Service Robotics / Ausgabe 3/2017
Print ISSN: 1861-2776
Elektronische ISSN: 1861-2784
DOI
https://doi.org/10.1007/s11370-017-0225-x

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