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Track Planning with Automatic Obstacle Recognition and Avoidance for Maritime...
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Track Planning with Automatic Obstacle Recognition and Avoidance for Maritime Vessels

A special issue of Journal of Marine Science and Engineering (ISSN 2077-1312). This special issue belongs to the section "Ocean Engineering".

Deadline for manuscript submissions: 10 August 2024 | Viewed by 115

Special Issue Editor

Dr. Dimitrios V. Lyridis

E-Mail Website
Guest Editor
Laboratory for Maritime Transport, School of Naval Architecture and Marine Engineering, National Technical University of Athens, 15780 Athens, Greece
Interests: maritime transport; economics and finance; energy and the environment
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Machine learning and artificial intelligence (AI) have expanded to several fields, from robotics to economic models, and enabled real-time algorithms to help plan the course of autonomous, non-autonomous, manned, or unmanned aircraft and surface vehicles. Especially for maritime vessels, and with automation and digitalization becoming increasingly central in their operation, optimum routing, path planning, and collision (with vessels, large objects, or large marine mammals) avoidance in complex sea environments emerge as areas where AI can play a pivotal role; in addition, multi-objective optimization algorithms, fuzzy logic, and other mathematical tools can solve complex problems in a practical and applied manner for use by modern marine vehicles.

Dr. Dimitrios V. Lyridis
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Journal of Marine Science and Engineering is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • optimum routing
  • path planning
  • marine vehicles
  • AI

Published Papers (1 paper)

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Research

17 pages, 14824 KiB  
Article
Model Predictive Collision Avoidance Control for Object Transport of Unmanned Underwater Vehicle-Dual-Manipulator Systems
by Yingxiang Wang and Jian Gao
J. Mar. Sci. Eng. 2024, 12(6), 926; https://doi.org/10.3390/jmse12060926 (registering DOI) - 31 May 2024
Abstract
Unmanned underwater vehicle-dual-manipulator systems (UVDMSs) have attracted much research due to their humanoid operation capabilities, which have the advantage of cooperative manipulations and transporting underwater objects. Meanwhile, collision avoidance of UVDMSs is more challenging than that of unmanned underwater vehicle-dual manipulator systems (UVMSs). [...] Read more.
Unmanned underwater vehicle-dual-manipulator systems (UVDMSs) have attracted much research due to their humanoid operation capabilities, which have the advantage of cooperative manipulations and transporting underwater objects. Meanwhile, collision avoidance of UVDMSs is more challenging than that of unmanned underwater vehicle-dual manipulator systems (UVMSs). In this work, a model predictive control (MPC) approach is proposed for collision avoidance in objects transporting tasks of UVDMSs. The minimum distances of mutual manipulators and frame obstacles are handled as velocity constraints in the optimization of the UVDMS’s object tracking control. The command velocity generated by the model predictive kinematic controller is tracked by a dynamic inversion control scheme while model uncertainties are compensated by a neural network. Moreover, the tracking errors of the proposed dynamic controller are proved to be convergent by the Lyapunov method. At last, a three-dimensional (3D) UVDMS simulation platform is developed to verify the effectiveness of the proposed control strategy in the tasks of collision avoidance and object transport. Full article
(This article belongs to the Special Issue Track Planning with Automatic Obstacle Recognition and Avoidance for Maritime Vessels)
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