underwater vehicle
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2022 ◽  
Vol 120 ◽  
pp. 102925
Rui Hu ◽  
Di Lu ◽  
Chengke Xiong ◽  
Chenxin Lyu ◽  
Hexiong Zhou ◽  

2022 ◽  
Vol 245 ◽  
pp. 110489
Zhaoyu Qu ◽  
Nana Yang ◽  
Xiongliang Yao ◽  
Guihui Ma ◽  
Yingyu Chen ◽  

2022 ◽  
Vol 15 ◽  
Chensheng Cheng ◽  
Can Wang ◽  
Dianyu Yang ◽  
Weidong Liu ◽  
Feihu Zhang

SLAM (Simultaneous Localization And Mapping) plays a vital role in navigation tasks of AUV (Autonomous Underwater Vehicle). However, due to a vast amount of image sonar data and some acoustic equipment's inherent high latency, it is a considerable challenge to implement real-time underwater SLAM on a small AUV. This paper presents a filter based methodology for SLAM algorithms in underwater environments. First, a multi-beam forward looking sonar (MFLS) is utilized to extract environmental features. The acquired sonar image is then converted to sparse point cloud format through threshold segmentation and distance-constrained filtering to solve the calculation explosion issue caused by a large amount of original data. Second, based on the proposed method, the DVL, IMU, and sonar data are fused, the Rao-Blackwellized particle filter (RBPF)-based SLAM method is used to estimate AUV pose and generate an occupancy grid map. To verify the proposed algorithm, the underwater vehicle is equipped as an experimental platform to conduct field tasks in both the experimental pool and wild lake, respectively. Experiments illustrate that the proposed approach achieves better performance in both state estimation and suppressing divergence.

2022 ◽  
Vol 10 (1) ◽  
pp. 66
Sung-Jo Yun ◽  
Hyo-Gon Kim ◽  
Jung-Woo Park ◽  
Hyo-Jun Lee ◽  
Jong-Chan Kim ◽  

Owing to environmental constraints, it is challenging to stably conduct various missions or surveys of the seabed for a prolonged period in the marine environment. To address this challenge, several devices and technologies are being developed. In this study, we aimed to develop an unmanned underwater vehicle (UUV)—specifically, a towed underwater platform—that can be loaded and unloaded via joint operation with an unmanned surface vehicle, which can be connected to a wired cable to obtain a stable power supply and high-speed communication. In addition, various sensors for detection are employed to investigate the marine environment and conduct missions. Furthermore, we operated the developed UUV in actual waters, reviewed the results, and examined its practical operability.

2022 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Serhat Yilmaz ◽  
Gülten Altıokka Yılmaz

Purpose The development of robust control algorithms for the position, velocity and trajectory control of unmanned underwater vehicles (UUVs) depends on the accuracy of their mathematical models. Accuracy of the model is determined by precise estimation of the UUV hydrodynamic parameters. The purpose of this study is to determine the hydrodynamic forces and moments acting on an underwater vehicle with complex body geometry and moving at low speeds and to achieve the accurate coefficients associated with them. Design/methodology/approach A three-dimensional (3D) computer-aided design (CAD) model of UUV is designed with one-to-one dimensions. 3D fluid flow simulations are conducted using computational fluid dynamics (CFD) software programme in the solution of Navier Stokes equations for laminar and turbulent flow analysis. The coefficients depending on the hydrodynamic forces and moments are determined by the external flow analysis using the CFD programme. The Flow Simulation k-ε turbulence model is used for the transition from laminar flow to turbulent flow. Hydrodynamic properties such as lift and drag coefficients and roll and yaw moment coefficients are calculated. The parameters are compared with the coefficient values found by experimental methods. Findings Although the modular type UUV has a complex body geometry, the comparative results of the experiments and simulations confirm that the defined model parameters are accurate and close to the actual experimental values. In the proposed k-ε method, the percentage error in the estimation of drag and lifting coefficients is decreased to 4.2% and 8.39%, respectively. Practical implications The model coefficients determined in this study can be used in high-level control simulations which leads to the development of robust real-time controllers for complex-shaped modular UUVs. Originality/value The Lucky Fin UUV with 4 degrees of freedom is a specific design and its CAD model is first extracted. Verification of simulation results by experiments is generally less referenced in studies. However, it provides more precise parameter identification of the model. Proposed study offers a simple and low-cost experimental measurement method for verification of the hydrodynamic parameters. The extracted model and coefficients are worthwhile references for the analysis of modular type UUVs.

Mitzi Alcaraz-Carrazco ◽  
Jorge Gudiño-Lau ◽  
Óscar Issac-Zamora ◽  
Saida M. Charre-Ibarra ◽  
Janeth A. Alcalá-Rodríguez ◽  

En los últimos años las investigaciones del área de mecatrónica están enfocados a la exploración marina, por lo que muchos centros de investigaciones y escuelas han encaminado sus trabajos al desarrollo de robots submarinos no tripulados y operados remotamente, también conocidos como ROUV por su acrónimo en inglés Remotely Operated Underwater Vehicle (Vehículo submarino operado remotamente). Este artículo muestra la historia de los vehículos operados remotamente ROV (Remotely Operated Vehicle), así como la clasificación, una breve descripción y aplicación de los robots submarinos no tripulados que han trascendido en el área de la mecatrónica. Por último, se describe el diseño de un robot submarino no tripulado en 3D para la exploración marina.

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