RT Journal Article
T1 UAV trajectory optimization for Minimum Time Search with communication constraints and collision avoidance
A1 Perez-Carabaza, Sara
A1 Scherer, Jürgen
A1 Rinner, Bernhard
A1 López Orozco, José Antonio
A1 Besada Portas, Eva
AB Minimum Time Search (MTS) algorithms help in search missions proposing search trajectories that minimize the target detection time considering the available information about the search scenario. This work proposes a MTS planner based on ant colony optimization that includes communication and collision avoidance constraints. This ensures that the Unmanned Aerial Vehicles (UAVs) are able to complete the optimized search trajectories without risk of collision or loss of communication with the ground control station. This approach is a great advantage nowadays, where UAVs flight regulation is quite strict, often requiring to monitor the state of the UAVs during the whole mission, impeding UAV deployments without continuous communication to the ground control station. The proposed algorithm is tested with several search scenarios and compared against two state of the art techniques based on Cross Entropy Optimization and Genetic Algorithms, which have been adapted to make them consider collision and communication constraints as well.
PB Elsevier
SN 0952-1976
YR 2019
FD 2019
LK https://hdl.handle.net/20.500.14352/96652
UL https://hdl.handle.net/20.500.14352/96652
LA eng
NO Sara Pérez-Carabaza, Jürgen Scherer, Bernhard Rinner, José A. López-Orozco, Eva Besada-Portas, UAV trajectory optimization for Minimum Time Search with communication constraints and collision avoidance, Engineering Applications of Artificial Intelligence, Volume 85, 2019, Pages 357-371, ISSN 0952-1976, https://doi.org/10.1016/j.engappai.2019.06.002.
NO El texto completo de este trabajo no se encuentra disponible por no haber sido facilitado aún por su autor, por restricciones de copyright, o por no existir una versión digital.
NO Airbus
NO University of Klagenfurt
DS Docta Complutense
RD 16 abr 2025