Waypoint planning with Dubins Curves using Genetic Algorithms

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Abstract

Mission planning for aircraft is often done as waypoint planning. A sequence of waypoints describing the three-dimensional positions that the aircraft must visit. A common approach is to plan the sequence of the waypoints such that the Euclidean distance between them is minimized. When the high-level waypoint planning is finished, a finer grained planning is executed to obtain a trajectory that the aircraft must follow. When the waypoints in a plan are distributed far apart compared to the turning radius of the aircraft, the two- step planning approach works well, but when the waypoints are closer, the kinematics of the aircraft ruins the plan. This work describes an approach that uses a genetic algorithm to solve the waypoint planning problem while considering the kinematics of the aircraft in one single step. This approach entails the addition of a heading and target speed along with the position in the waypoint definition. The kinematics of the aircraft is modeled with Dubins curves, which are extended to allow variable turning radii.
Original languageEnglish
Title of host publicationEuropean Control Conference (ECC), 2016
PublisherIEEE
Publication dateJun 2016
Pages2240-2246
ISBN (Electronic)978-1-5090-2591-6
DOIs
Publication statusPublished - Jun 2016
EventEuropean Control Conference 2016 - Aalborg, Denmark
Duration: 28 Jun 20161 Jul 2016

Conference

ConferenceEuropean Control Conference 2016
CountryDenmark
CityAalborg
Period28/06/201601/07/2016

Cite this

Hansen, Karl Damkjær ; La Cour-Harbo, Anders. / Waypoint planning with Dubins Curves using Genetic Algorithms. European Control Conference (ECC), 2016. IEEE, 2016. pp. 2240-2246
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Hansen, KD & La Cour-Harbo, A 2016, Waypoint planning with Dubins Curves using Genetic Algorithms. in European Control Conference (ECC), 2016. IEEE, pp. 2240-2246, European Control Conference 2016, Aalborg, Denmark, 28/06/2016. https://doi.org/10.1109/ECC.2016.7810624

Waypoint planning with Dubins Curves using Genetic Algorithms. / Hansen, Karl Damkjær; La Cour-Harbo, Anders.

European Control Conference (ECC), 2016. IEEE, 2016. p. 2240-2246.

Research output: Contribution to book/anthology/report/conference proceedingArticle in proceedingResearchpeer-review

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