TY  - JOUR
A1  - Thoma, Andreas
A1  - Thomessen, Karolin
A1  - Gardi, Alessandro
A1  - Fisher, A.
A1  - Braun, Carsten
T1  - Prioritising paths: An improved cost function for local path planning for UAV in medical applications
JF  - The Aeronautical Journal
N2  - 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.
KW  - Path planning
KW  - Cost function
KW  - Multi-objective optimization
Y1  - 2023
U6  - http://dx.doi.org/10.1017/aer.2023.68
SN  - 0001-9240 (Print)
SN  - 2059-6464 (Online)
IS  - First View
SP  - 1
EP  - 18
PB  - Cambridge University Press
CY  - Cambridge
ER  -