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.
A Modular Autonomous Driving System for Electric Boats based on Fuzzy Controllers and Q-Learning / Ferrandino, Emanuele; Capillo, Antonino; DE SANTIS, Enrico; FRATTALE MASCIOLI, Fabio Massimo; Rizzi, Antonello. - (2021), pp. 185-195. (Intervento presentato al convegno 13th International Joint Conference on Computational Intelligence - FCTA tenutosi a Online streaming) [10.5220/0010678100003063].
A Modular Autonomous Driving System for Electric Boats based on Fuzzy Controllers and Q-Learning
Emanuele Ferrandino;Antonino Capillo;Enrico De Santis;Fabio Massimo Frattale 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.File | Dimensione | Formato | |
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