Title Intelligent Online Learning Strategy for an Autonomous Surface Vehicle in Lake Environments Using Evolutionary Computation
Authors Arzamendia M., GUTIÉRREZ REINA, DANIEL, Toral S., Gregor D., Asimakopoulou E., Bessis N., GUTIÉRREZ REINA, DANIEL
External publication No
Means IEEE Intell. Transp. Syst. Mag.
Scope Article
Nature Científica
JCR Quartile 2
SJR Quartile 1
JCR Impact 3.36300
Area International
Web https://www.scopus.com/inward/record.uri?eid=2-s2.0-85077771794&doi=10.1109%2fMITS.2019.2939109&partnerID=40&md5=0b6f9c49b48bce380ca8b47099f95343
Publication date 01/01/2019
ISI 000498021600012
Scopus Id 2-s2.0-85077771794
DOI 10.1109/MITS.2019.2939109
Abstract An artificial intelligence strategy for the localization and monitoring of pollution-caused events caused by contamination in a lake, of a system consisting of an Autonomous Surface Vehicle (ASV) and a network of wireless beacons is proposed and evaluated. Particularly the event of algae bloom is considered. For this purpose, the path planning of the ASV is calculated at different phases with the help of an evolutionary algorithm. The main novelty of the proposed strategy is that it follows an intelligent online learning approach. Therefore, the ASV learns from the environment and makes decisions depending on the collected data. The proposed path planning is based on the adaption of the travelling salesman problem with constraints, using the beacons as geo-localization references and information support infrastructure. The approach consists of different phases that balance the exploration of the lake for searching new events and the exploitation of already discovered ones. A suitable configuration of the fitness function allows an efficient balance between exploration and intensification. Simulation results show that the level of coverage achieved are at least 85% for a situation where up to two dynamic algae blooms occurred at different locations in the lake. © 2009-2012 IEEE.
Keywords Algae; E-learning; Lakes; Motion planning; Traveling salesman problem; Unmanned surface vehicles; Algae blooms; Autonomous surface vehicles; Fitness functions; Information support; Online learning; On
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