This article studies the design, modeling, and implementation challenges of a path-following with obstacle avoidance algorithms as Guidance, Navigation, and Control (GNC) architecture of an Unmanned Surface Vehicle (USV) in harbor conditions. First, an effective mathematical model is developed based on System Identification (SI), validating the USV model with field-test data. Then, a guidance system is addressed based on a Line-Of-Sight (LOS) algorithm, which uses a LiDAR as the main perception sensor for the obstacle avoidance algorithm. The GNC architecture uses a modular approach, including obstacle detection, path-following, and control in the USV platform. Finally, an implementation challenge in two control scenarios, simulation and field-test, is addressed to validate the designed GNC architecture.

This article studies the design, modeling, and implementation challenges for a target detection algorithm using multi-sensor technology of a co-operative autonomous offshore system, formed by an unmanned surface vehicle (USV) and an autonomous underwater vehicle (AUV). First, the study develops an accurate mathematical model of the USV to be included as a simulation environment for testing the guidance, navigation, and control (GNC) algorithm. Then, a guidance system is addressed based on an underwater coverage path for the AUV, which uses a mechanical imaging sonar as the primary AUV perception sensor and ultra-short baseline (USBL) as a positioning system. Once the target is detected, the AUV sends its location to the USV, which creates a straight-line for path following with obstacle avoidance capabilities, using a LiDAR as the main USV perception sensor. This communication in the co-operative autonomous offshore system includes a decentralized Robot Operating System (ROS) framework with a master node at each vehicle. Additionally, each vehicle uses a modular approach for the GNC architecture, including target detection, path-following, and guidance control modules. Finally, implementation challenges in a field test scenario involving both AUV and USV are addressed to validate the target detection algorithm.

Automated systems have been seamlessly integrated into several industries as part of their industrial automation processes. Employing automated systems, such as autonomous vehicles, allows industries to increase productivity, benefit from a wide range of technologies and capabilities, and improve workplace safety. So far, most of the existing systems consider utilizing one type of autonomous vehicle. In this work, we propose a collaboration of different types of unmanned vehicles in maritime offshore scenarios. Providing high capacity, extended coverage, and better quality of services, autonomous collaborative systems can enable emerging maritime use cases, such as remote monitoring and navigation assistance. Motivated by these potential benefits, we propose the deployment of an Unmanned Surface Vehicle (USV) and an Unmanned Aerial Vehicle (UAV) in an autonomous collaborative communication system. Specifically, we design high-speed, directional communication links between a terrestrial control station and the two unmanned vehicles. Using measurement and simulation results, we evaluate the performance of the designed links in different communication scenarios and we show the benefits of employing multiple autonomous vehicles in the proposed communication system.

This article studies the design, modeling, and implementation of a path-following algorithm as a guidance, navigation, and control (GNC) architecture for an autonomous underwater vehicle (AUV). First, a mathematical model is developed based on nonlinear equations of motion and parameter estimation techniques, including the model validation based on field test data. Then, the guidance system incorporates a line-of-sight (LOS) algorithm with a combination of position PID controllers. The GNC architecture includes a modular and multi-layer approach with an LOS-based, path-following algorithm in the AUV platform. Furthermore, the navigation used in the path-following algorithm is developed based on a predefined coverage area. Finally, this study addresses simulation and field test control scenarios to verify the developed GNC architecture.

The aim of this study is to implement a modelbased control architecture for a twin jet Unmanned Surface Vessel (USV) using the line-of-sight (LOS) path algorithm for straight-line. The modeling and design of the motion control system are studied using MATLAB-Simulink and the real-time implementation is done by using Robot Operating System (ROS). To simplify the real-time implementation and thus, programming files, the necessary code generation is done by generating a Standalone ROS Node from Simulink software, making the process easier for researchers with non-advanced programming skills. Simulation and field test results are shown to validate the model-based control architecture.

The aim of this study is to analyse the modular mechanical design and integration of all three low-level modules in UX-1 (pendulum, ballast system and propulsion unit). The components of the perception and navigation systems have position and orientation requirements that dictate the shape of the hull. A structural strength analysis using Finite Element method (FEM) was made to study the hull strength during deep dives. The results are presented here, which indicates that the hull endures pressures related to deep dives. Also for validation, strain gauge locations were defined.