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Search Results (4)

Search Parameters:
Keywords = 3DOF ASV

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27 pages, 3626 KiB  
Article
A Novel COLREGs-Based Automatic Berthing Scheme for Autonomous Surface Vessels
by Shouzheng Yuan, Gongwu Sun, Yunqian He, Yuxin Sun, Simeng Song, Wanyuan Zhang and Huifeng Jiao
J. Mar. Sci. Eng. 2025, 13(5), 903; https://doi.org/10.3390/jmse13050903 - 30 Apr 2025
Viewed by 395
Abstract
This paper tackles the highly challenging problem of automatic berthing for autonomous surface vessels (ASVs), encompassing trajectory planning, trajectory tracking, and collision avoidance. Firstly, a novel A* algorithm integrated with a quasi-uniform B-spline and quadratic interpolation method (A*QB) is proposed for generating a [...] Read more.
This paper tackles the highly challenging problem of automatic berthing for autonomous surface vessels (ASVs), encompassing trajectory planning, trajectory tracking, and collision avoidance. Firstly, a novel A* algorithm integrated with a quasi-uniform B-spline and quadratic interpolation method (A*QB) is proposed for generating a smooth trajectory from the initial position to the berth, utilizing an offline-generated scaled map. Secondly, the optimal nonlinear model predictive control (NMPC)-based trajectory-tracking framework is established, incorporating the model’s uncertainty, the input saturation, and environmental disturbances, based on a 3-DOF model of a ship. Finally, considering the collision risks during port berthing, a COLREGs-based collision avoidance method is investigated. Consequently, a novel trajectory-tracking and COLREGs-based collision avoidance (TTCCA) scheme is proposed, ensuring that the ASV navigates along the desired trajectory, safely avoids both static and dynamic obstacles, and successfully reaches the berth. To validate the TTCCA approach, numerical simulations are conducted across four scenarios with comparisons to existing methods. The experimental results demonstrate the effectiveness and superiority of the proposed scheme. Full article
(This article belongs to the Section Ocean Engineering)
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26 pages, 1534 KiB  
Article
Performance Comparison of Meta-Heuristics Applied to Optimal Signal Design for Parameter Identification
by Accacio Ferreira dos Santos Neto, Murillo Ferreira dos Santos, Mathaus Ferreira da Silva, Leonardo de Mello Honório, Edimar José de Oliveira and Edvaldo Soares Araújo Neto
Sensors 2023, 23(22), 9085; https://doi.org/10.3390/s23229085 - 10 Nov 2023
Cited by 2 | Viewed by 1278
Abstract
This paper presents a comparative study that explores the performance of various meta-heuristics employed for Optimal Signal Design, specifically focusing on estimating parameters in nonlinear systems. The study introduces the Robust Sub-Optimal Excitation Signal Generation and Optimal Parameter Estimation (rSOESGOPE) methodology, which is [...] Read more.
This paper presents a comparative study that explores the performance of various meta-heuristics employed for Optimal Signal Design, specifically focusing on estimating parameters in nonlinear systems. The study introduces the Robust Sub-Optimal Excitation Signal Generation and Optimal Parameter Estimation (rSOESGOPE) methodology, which is originally derived from the well-known Particle Swarm Optimization (PSO) algorithm. Through a real-life case study involving an Autonomous Surface Vessel (ASV) equipped with three Degrees of Freedom (DoFs) and an aerial holonomic propulsion system, the effectiveness of different meta-heuristics is thoroughly evaluated. By conducting an in-depth analysis and comparison of the obtained results from the diverse meta-heuristics, this study offers valuable insights for selecting the most suitable optimization technique for parameter estimation in nonlinear systems. Researchers and experimental tests in the field can benefit from the comprehensive examination of these techniques, aiding them in making informed decisions about the optimal approach for optimizing parameter estimation in nonlinear systems. Full article
(This article belongs to the Section Sensors and Robotics)
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22 pages, 12194 KiB  
Article
A ROS-Based GNC Architecture for Autonomous Surface Vehicle Based on a New Multimission Management Paradigm
by Vincenzo D’Angelo, Paolo Folino, Marco Lupia, Gianfranco Gagliardi, Gianni Cario, Francesco Cicchello Gaccio and Alessandro Casavola
Drones 2022, 6(12), 382; https://doi.org/10.3390/drones6120382 - 27 Nov 2022
Cited by 6 | Viewed by 3546
Abstract
This paper presents the design and implementation of BAICal (Intelligent Autonomous Buoy by the University of Calabria), an autonomous surface vehicle (ASV) developed at the Autonomous Systems Lab (LASA) of the Department of Computer Science, Modeling, Electronics, and Systems Engineering (DIMES), University of [...] Read more.
This paper presents the design and implementation of BAICal (Intelligent Autonomous Buoy by the University of Calabria), an autonomous surface vehicle (ASV) developed at the Autonomous Systems Lab (LASA) of the Department of Computer Science, Modeling, Electronics, and Systems Engineering (DIMES), University of Calabria. The basic project was born as a research program in marine robotics with multiple applications, either in the sea or in lake/river environments, for data monitoring, search and rescue operations and diver support tasks. Mechanical and hardware designs are discussed by considering a three-degree-of-freedom (3DoF) dynamical model of the vehicle. An extension to the typical guidance, navigation, and control (GNC) software architecture is presented. The software design and the implementation of a manager module (M-GNC architecture) that allows the vehicle to autonomously coordinate missions are described. Indeed, autonomous guidance and movement are only one of several more complex tasks that mobile robots have to perform in a real scenario and that allow a long-term life cycle. Module-based software architecture is developed by using the Robot Operating System (ROS) framework that is suitable for different kinds of autonomous vehicles, such as aerial, ground, surface or underwater drones. Full article
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19 pages, 4356 KiB  
Article
Hull and Aerial Holonomic Propulsion System Design for Optimal Underwater Sensor Positioning in Autonomous Surface Vessels
by Bruno A. Regina, Leonardo M. Honório, Antônio A. N. Pancoti, Mathaus F. Silva, Murillo F. Santos, Vitor M. L. Lopes, Accacio F. Santos Neto and Luis G. F. Westin
Sensors 2021, 21(2), 571; https://doi.org/10.3390/s21020571 - 15 Jan 2021
Cited by 20 | Viewed by 3802
Abstract
Acoustic Doppler Current Profiler (ADCP) sensors measure water inflows and are essential to evaluate the Flow Curve (FC) of rivers. The FC is used to calibrate hydrological models responsible for planning the electrical dispatch of all power plants in several countries. Therefore, errors [...] Read more.
Acoustic Doppler Current Profiler (ADCP) sensors measure water inflows and are essential to evaluate the Flow Curve (FC) of rivers. The FC is used to calibrate hydrological models responsible for planning the electrical dispatch of all power plants in several countries. Therefore, errors in those measures propagate to the final energy cost evaluation. One problem regarding this sensor is its positioning on the vessel. If placed on the bow, it becomes exposed to flowing obstacles, and if it is installed on the stern, the redirected water from the boat and its propulsion system change the sensor readings. To improve the sensor readings, this paper proposes the design of a catamaran-like Autonomous Surface Vessel (ASV) with an optimized hull design, aerial propulsion, and optimal sensor placement to keep them protected and precise, allowing inspections in critical areas such as ultra-shallow waters and mangroves. Full article
(This article belongs to the Section Remote Sensors)
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