TY - JOUR
T1 - MODELLING SAND RIPPLES IN MINE COUNTERMEASURE SIMULATIONS BY MEANS OF STOCHASTIC OPTIMAL CONTROL
AU - Blondeel, P.
AU - Van Utterbeeck, F.
AU - Lauwens, B.
N1 - Publisher Copyright:
© 2024, Scipedia S.L., All rights reserved.
PY - 2024
Y1 - 2024
N2 - Modelling and simulating mine countermeasures (MCM) search missions performed by autonomous vehicles equipped with a sensor capable of detecting mines at sea is a challenging endeavour. In this work, we present a novel way to model and account for sand ripples present on the bottom of the ocean while calculating trajectories for the autonomous vehicles by means of a stochastic optimal control framework. It is known from the scientific literature that these ripples impact the sea mine detection capabilities of the autonomous vehicles.
AB - Modelling and simulating mine countermeasures (MCM) search missions performed by autonomous vehicles equipped with a sensor capable of detecting mines at sea is a challenging endeavour. In this work, we present a novel way to model and account for sand ripples present on the bottom of the ocean while calculating trajectories for the autonomous vehicles by means of a stochastic optimal control framework. It is known from the scientific literature that these ripples impact the sea mine detection capabilities of the autonomous vehicles.
KW - Mine Countermeasures
KW - Sand Ripples
KW - Stochastic Optimal Control
UR - https://www.scopus.com/pages/publications/105012422842
U2 - 10.23967/eccomas.2024.237
DO - 10.23967/eccomas.2024.237
M3 - Conference article
AN - SCOPUS:105012422842
SN - 2696-6999
JO - World Congress in Computational Mechanics and ECCOMAS Congress
JF - World Congress in Computational Mechanics and ECCOMAS Congress
T2 - 9th European Congress on Computational Methods in Applied Sciences and Engineering, ECCOMAS 2024
Y2 - 3 June 2024 through 7 June 2024
ER -