scholarly journals Evaluation of an Efficient Approach for Target Tracking from Acoustic Imagery for the Perception System of an Autonomous Underwater Vehicle

10.5772/56954 ◽  
2014 ◽  
Vol 11 (2) ◽  
pp. 24 ◽  
Author(s):  
Sebastián A. Villar ◽  
Gerardo G. Acosta ◽  
André L. Sousa ◽  
Alejandro Rozenfeld
Keyword(s):  
Target Tracking ◽  
Autonomous Underwater Vehicle ◽  
Underwater Vehicle ◽  
Efficient Approach ◽  
Perception System

scholarly journals BOTNet: Deep Learning-Based Bearings-Only Tracking Using Multiple Passive Sensors

Sensors ◽  
2021 ◽  
Vol 21 (13) ◽  
pp. 4457
Author(s):  
Hadar Shalev ◽  
Itzik Klein
Keyword(s):  
Deep Learning ◽  
Least Squares ◽  
Target Tracking ◽  
Autonomous Underwater Vehicle ◽  
Target Position ◽  
Underwater Vehicle ◽  
Traffic Monitoring ◽  
Vehicle Simulation ◽  
Passive Sensors ◽  
Least Squares Algorithm

Bearings-only target tracking is commonly used in many fields, like air or sea traffic monitoring, tracking a member in a formation, and military applications. When tracking with synchronous passive multisensor systems, each sensor provides a line-of-sight measurement. They are plugged into an iterative least squares algorithm to estimate the unknown target position vector. Instead of using iterative least squares, this paper presents a deep-learning based framework for the bearing-only target tracking process, applicable for any bearings-only target tracking task. As a data-driven method, the proposed deep-learning framework offers several advantages over the traditional iterative least squares. To demonstrate the proposed approach, a scenario of tracking an autonomous underwater vehicle approaching an underwater docking station is considered. There, several passive sensors are mounted near a docking station to enable accurate localization of an approaching autonomous underwater vehicle. Simulation results show the proposed framework obtains better accuracy compared to the iterative least squares algorithm.

scholarly journals Target tracking control of underactuated autonomous underwater vehicle based on adaptive nonsingular terminal sliding mode control

2020 ◽  
Vol 17 (2) ◽  
pp. 172988142091994
Author(s):  
Jian Cao ◽  
Yushan Sun ◽  
Guocheng Zhang ◽  
Wenlong Jiao ◽  
Xiangbin Wang ◽  
...  
Keyword(s):  
Sliding Mode Control ◽  
Target Tracking ◽  
Tracking Control ◽  
Autonomous Underwater Vehicle ◽  
Sliding Mode ◽  
Underwater Vehicle ◽  
Terminal Sliding Mode Control ◽  
Terminal Sliding Mode ◽  
Nonsingular Terminal Sliding Mode ◽  
Tracking Controller

This article addresses the design of adaptive target tracking control for an underactuated autonomous underwater vehicle subject to uncertain dynamics and external disturbances induced by ocean current. Firstly, based on the line-of-sight method, the moving target tracking guidance strategy is designed, and the target tracking reference speed and reference angular velocity are given. According to the obtained reference speed and reference angular velocities, the reference control quantity is differentiated and filtered based on dynamic surface control. The target tracking controller is designed based on radial basis function neural network and nonsingular terminal sliding mode control and adaptive techniques. Lyapunov stability principle is utilized to ensure the asymptotic stability of the target tracking controller. Simulation of target tracking is carried out to illustrate the effectiveness of the proposed controller.

Development of a Semi-Autonomous Underwater Vehicle for Intervention Missions (SAUVIM Phase III-B)

2009 ◽  
Author(s):  
Giacomo Marani ◽  
Junku Yuh ◽  
Song K. Choi ◽  
Son-Cheol Yu ◽  
Luca Gambella ◽  
...  
Keyword(s):  
Autonomous Underwater Vehicle ◽  
Underwater Vehicle ◽  
Phase Iii
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