A Modular Autonomous Driving System for Electric Boats based on Fuzzy Controllers and Q-Learning

Emanuele Ferrandino, Antonino Capillo, Enrico De Santis, Fabio Mascioli, Antonello Rizzi

2021

Abstract

This paper describes the architecture and control design of an autonomous Electric Boat, together with a specific simulation environment for training and testing the Fuzzy Inference Systems. The boat will be in charge to exit and enter from harbors, plan and follow a route, avoid obstacles such as other boats, correct its motion, perform a virtual anchor and switch between these operations autonomously. The boat is equipped with a set of smart sensors such as sonars, a Global Positioning System, a camera-based vision system and an Inertial Measurement Unit. General navigation rules are respected during the route. We propose an architecture integrating several Fuzzy Controller-based modular pipelines. Furthermore, we propose a mathematical formalization of the Fish Schooling Behavior useful for training Fuzzy Controllers through Q-Learning. Our architecture will soon be implemented on a real boat intended for navigating in inland waters.

Paper Citation

in Harvard Style

Ferrandino E., Capillo A., De Santis E., Mascioli F. and Rizzi A. (2021). A Modular Autonomous Driving System for Electric Boats based on Fuzzy Controllers and Q-Learning. In Proceedings of the 13th International Joint Conference on Computational Intelligence (IJCCI 2021) - Volume 1: FCTA; ISBN 978-989-758-534-0, SciTePress, pages 185-195. DOI: 10.5220/0010678100003063

in Bibtex Style

@conference{fcta21,
author={Emanuele Ferrandino and Antonino Capillo and Enrico De Santis and Fabio Mascioli and Antonello Rizzi},
title={A Modular Autonomous Driving System for Electric Boats based on Fuzzy Controllers and Q-Learning},
booktitle={Proceedings of the 13th International Joint Conference on Computational Intelligence (IJCCI 2021) - Volume 1: FCTA},
year={2021},
pages={185-195},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010678100003063},
isbn={978-989-758-534-0},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 13th International Joint Conference on Computational Intelligence (IJCCI 2021) - Volume 1: FCTA
TI - A Modular Autonomous Driving System for Electric Boats based on Fuzzy Controllers and Q-Learning
SN - 978-989-758-534-0
AU - Ferrandino E.
AU - Capillo A.
AU - De Santis E.
AU - Mascioli F.
AU - Rizzi A.
PY - 2021
SP - 185
EP - 195
DO - 10.5220/0010678100003063
PB - SciTePress