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Authors: Emanuele Ferrandino ; Antonino Capillo ; Enrico De Santis ; Fabio Mascioli and Antonello Rizzi

Affiliation: Department of Information Engineering, Electronics and Telecommunications (DIET), University of Rome “La Sapienza”, Via Eudossiana 18, 00184 Rome, Italy

Keyword(s): Electric Boat, Autonomous Driving System, Finite State Machine, Autopilot, Obstacle Detection, Obstacle Avoidance, Motion Control, Virtual Anchor, Q-Learning, Fuzzy Controller, Fish Schooling Behavior.

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.

CC BY-NC-ND 4.0

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Paper citation in several formats:
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) - FCTA; ISBN 978-989-758-534-0; ISSN 2184-3236, SciTePress, pages 185-195. DOI: 10.5220/0010678100003063

@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) - FCTA},
year={2021},
pages={185-195},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010678100003063},
isbn={978-989-758-534-0},
issn={2184-3236},
}

TY - CONF

JO - Proceedings of the 13th International Joint Conference on Computational Intelligence (IJCCI 2021) - FCTA
TI - A Modular Autonomous Driving System for Electric Boats based on Fuzzy Controllers and Q-Learning
SN - 978-989-758-534-0
IS - 2184-3236
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