Analysis of coordination modes for multi-UUV based on Model Driven Architecture

Soriano, Thierry; Pham, Hoang Anh; Ngo, Van Hien

doi:10.1109/mecatronics.2018.8495893

Cited by 4 publications

(3 citation statements)

References 15 publications

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“…Stateflow, a Matlab/Simulink package that models decision logic through state machines, was also used to develop a Model Driven Architecture for multi-vehicle coordination avoiding collisions which communicate through ROS with UUV Simulator [119]. In some applications, vehicles need the ability to communicate, but if Radio Frequency is used, the distance that these vehicles can operate is minimal.…”

Section: B Uuv Simulatormentioning

confidence: 99%

Underwater Simulators Analysis for Digital Twinning

Ciuccoli,

Screpanti,

Scaradozzi

2024

IEEE Access

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The underwater environment is among Earth's most challenging domains, where failures incur elevated risks and costs for both technology and human endeavors. As a consequence, forecasting the behavior of mechatronic systems through simulation has become increasingly important. Underwater Robotic Simulators (URSs) allow researchers and engineers to safely develop and assess submarine systems. The selection of an appropriate URS from the list of available tools is not trivial. Moreover, the integration of this software with the Digital Twin (DT) concept presents numerous advantages, particularly the ability to link the simulated environment with actual underwater vehicles. This connection is facilitated by performing validation and simulation tests using Software In the Loop (SIL), Model In the Loop, and Hardware In the Loop (HIL) techniques. This paper extensively reviews URSs in the context of both robots and unmanned vehicles in light of the DT paradigm. The article critically examines distinctions among existing URSs, offering valuable insights to aid researchers in selecting the most fitting tool for their specific applications. Additionally, the review explores the practical applications of the identified simulators, categorizing their usage across different fields to illuminate the preferences within the scientific community and showcase prominent case studies.

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Section: B Uuv Simulatormentioning

confidence: 99%

Underwater Simulators Analysis for Digital Twinning

Ciuccoli,

Screpanti,

Scaradozzi

2024

IEEE Access

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“…In this case, we tested a straight-line flight control of the vehicle in the air. Set the original position O(0, 0, 0) of the vehicle on the water surface and the target position at the inertia coordinates T (5,5,5) in the air, and the route is a straight way from O to T. Consequently, the position response curve and attitude response curves can be obtained, shown in Figures 6 and 7, respectively.…”

Section: Air Position Responsementioning

confidence: 99%

“…Autonomous unmanned systems are very popular all over the world due to their broad range of applications such as surveillance, inspection, fast delivery, search and rescue, among many others [1][2][3]. In recent years, the rapid development of composite materials and the continuous upgrading of intelligent control technology have been of great help in the development of unmanned aerial vehicles (UAVs) and unmanned underwater vehicles (UUVs) [4,5]. More challenging, the unmanned aerial underwater vehicle (UAUV) has become a novel research field, which aims to design equipment that can fly in the air and navigate underwater.…”

Section: Introductionmentioning

confidence: 99%

System Modeling and Simulation of an Unmanned Aerial Underwater Vehicle

Chen

Liu

Meng

et al. 2019

JMSE

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Unmanned Aerial Underwater Vehicles (UAUVs) with multiple propellers can operate in two distinct mediums, air and underwater, and the system modeling of the autonomous vehicles is a key issue to adapt to these different external environments. In this paper, only a single set of aerial rotors with switching propulsion abilities are designed as driving components, and then a compound multi-model method is investigated to achieve good performance of the cross-medium motion. Furthermore, some additional variables, such as water resistance, buoyancy and their corresponding moments are considered for the underwater case. In particular, a critical coefficient for air-to-water switching is presented to express these gradually changing additional variables in the cross-medium motion process. Finally, the sliding mode control method is used to reduce the altitude error and attitude error of the vehicles with external environmental disturbances. The proposed scheme is tested and the model is verified on the simulation platform.

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A MBSE Application to Controllers of Autonomous Underwater Vehicles Based on Model-Driven Architecture Concepts

Hien

Truong

et al. 2020

Applied Sciences

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In this paper, a hybrid realization model is proposed for the controllers of autonomous underwater vehicles (AUVs). This model is based on the model-based systems engineering (MBSE) methodology, in combination with the model-driven architecture (MDA), the real-time unified modeling language (UML)/systems modeling language (SysML), the extended/unscented Kalman filter (EKF/UKF) algorithms, and hybrid automata, and it can be reused for designing controllers of various AUV types. The dynamic model and control structure of AUVs were combined with the specialization of MDA concepts as follows. The computation-independent model (CIM) was specified by the use-case model combined with the EKF/UKF algorithms and hybrid automata to intensively gather the control requirements. Then, the platform-independent model (PIM) was specialized using the real-time UML/SysML to design the capsule collaboration of control and its connections. The detailed PIM was subsequently converted into the platform-specific model (PSM) using open-source platforms to promptly realize the AUV controller. On the basis of the proposed hybrid model, a planar trajectory-tracking controller, which allows a miniature torpedo-shaped AUV to autonomously track the desired planar trajectory, was implemented and evaluated, and shown to have good feasibility.

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Analysis of coordination modes for multi-UUV based on Model Driven Architecture

Cited by 4 publications

References 15 publications

Underwater Simulators Analysis for Digital Twinning

Underwater Simulators Analysis for Digital Twinning

System Modeling and Simulation of an Unmanned Aerial Underwater Vehicle

A MBSE Application to Controllers of Autonomous Underwater Vehicles Based on Model-Driven Architecture Concepts

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