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.