TY  - JOUR
A1  - Thoma, Andreas
A1  - Gardi, Alessandro
A1  - Fisher, Alex
A1  - Braun, Carsten
T1  - Improving local path planning for UAV flight in challenging environments by refining cost function weights
T2  - CEAS Aeronautical Journal
N2  - Unmanned Aerial Vehicles (UAV) constantly gain in versatility. However, more reliable path planning algorithms are required until full autonomous UAV operation is possible. This work investigates the algorithm 3DVFH* and analyses its dependency on its cost function weights in 2400 environments. The analysis shows that the 3DVFH* can find a suitable path in every environment. However, a particular type of environment requires a specific choice of cost function weights. For minimal failure, probability interdependencies between the weights of the cost function have to be considered. This dependency reduces the number of control parameters and simplifies the usage of the 3DVFH*. Weights for costs associated with vertical evasion (pitch cost) and vicinity to obstacles (obstacle cost) have the highest influence on the failure probability of the local path planner. Environments with mainly very tall buildings (like large American city centres) require a preference for horizontal avoidance manoeuvres (achieved with high pitch cost weights). In contrast, environments with medium-to-low buildings (like European city centres) benefit from vertical avoidance manoeuvres (achieved with low pitch cost weights). The cost of the vicinity to obstacles also plays an essential role and must be chosen adequately for the environment. Choosing these two weights ideal is sufficient to reduce the failure probability below 10%.
KW  - Bio-inspired systems
KW  - Path planning
KW  - Obstacle avoidance
KW  - Unmanned aerial vehicles
Y1  - 2024
UR  - https://opus.bibliothek.fh-aachen.de/opus4/frontdoor/index/index/docId/11171
SN  - 1869-5590 (eISSN)
SN  - 1869-5582
N1  - Corresponding author: Andreas Thoma
PB  - Springer
CY  - Wien
ER  -