Prioritising paths: An improved cost function for local path planning for UAV in medical applications
- Even the shortest flight through unknown, cluttered environments requires reliable local path planning algorithms to avoid unforeseen obstacles. The algorithm must evaluate alternative flight paths and identify the best path if an obstacle blocks its way. Commonly, weighted sums are used here. This work shows that weighted Chebyshev distances and factorial achievement scalarising functions are suitable alternatives to weighted sums if combined with the 3DVFH* local path planning algorithm. Both methods considerably reduce the failure probability of simulated flights in various environments. The standard 3DVFH* uses a weighted sum and has a failure probability of 50% in the test environments. A factorial achievement scalarising function, which minimises the worst combination of two out of four objective functions, reaches a failure probability of 26%; A weighted Chebyshev distance, which optimises the worst objective, has a failure probability of 30%. These results show promise for further enhancements and to support broader applicability.
Verfasserangaben: | Andreas ThomaORCiD, Karolin Thomessen, Alessandro Gardi, A. Fisher, Carsten BraunORCiD |
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DOI: | https://doi.org/10.1017/aer.2023.68 |
ISSN: | 0001-9240 (Print) |
ISSN: | 2059-6464 (Online) |
Titel des übergeordneten Werkes (Englisch): | The Aeronautical Journal |
Verlag: | Cambridge University Press |
Verlagsort: | Cambridge |
Dokumentart: | Wissenschaftlicher Artikel |
Sprache: | Englisch |
Erscheinungsjahr: | 2023 |
Datum der Publikation (Server): | 22.08.2023 |
Freies Schlagwort / Tag: | Cost function; Multi-objective optimization; Path planning |
Ausgabe / Heft: | First View |
Erste Seite: | 1 |
Letzte Seite: | 18 |
Link: | https://doi.org/10.1017/aer.2023.68 |
Zugriffsart: | weltweit |
Fachbereiche und Einrichtungen: | FH Aachen / ECSM European Center for Sustainable Mobility |
FH Aachen / Fachbereich Luft- und Raumfahrttechnik | |
open_access (DINI-Set): | open_access |
collections: | Verlag / Cambridge University Press |
Open Access / Hybrid | |
Lizenz (Deutsch): | Creative Commons - Namensnennung |