Intelligent Online Learning Strategy for an Autonomous Surface Vehicle in Lake Environments Using Evolutionary Computation | Zendy

Mario Arzamendia | Zendy; Daniel Gutiérrez | Zendy; S. L. Toral | Zendy; Derlis Gregor | Zendy; Eleana Asimakopoulou | Zendy; Nik Bessis | Zendy

Open Access

Intelligent Online Learning Strategy for an Autonomous Surface Vehicle in Lake Environments Using Evolutionary Computation

Author(s) -

Mario Arzamendia,

Daniel Gutiérrez,

S. L. Toral,

Derlis Gregor,

Eleana Asimakopoulou,

Nik Bessis

Publication year - 2019

Publication title -

ieee intelligent transportation systems magazine

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.831

H-Index - 42

eISSN - 1941-1197

pISSN - 1939-1390

DOI - 10.1109/mits.2019.2939109

Subject(s) - beacon , motion planning , computer science , travelling salesman problem , evolution strategy , path (computing) , artificial intelligence , novelty , evolutionary computation , algal bloom , sonar , distributed computing , real time computing , ecology , computer network , algorithm , robot , philosophy , theology , phytoplankton , nutrient , biology

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 ...

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