Ocean Current-Aided Localization and Navigation for Underwater Gliders With Information Matching Algorithm

Zhang, Runfeng; Gao, Weiqiang; Yang, Shaoqiong; Wang, Yanhui; Lan, Shiquan; Yang, Xiuzhu

doi:10.1109/jsen.2021.3115789

Cited by 10 publications

(1 citation statement)

References 24 publications

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“…Another possible option would be to test using other disturbances, and checking what is the advantage of using FDE against CDE in these cases. Moreover, it could be possible to extend this work to more complex transition models, such as the ones shown in [39] or [40]. However, note that it would be needed to extend the disturbance models from the 2D models used in this work to 3D ones in order to match the aforementioned works.…”

Section: Discussionmentioning

confidence: 99%

An Efficient Underwater Navigation Method Using MPC with Unknown Kinematics and Non-Linear Disturbances

Barreno

Parras

Zazo

2023

JMSE

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Many Autonomous Underwater Vehicles (AUVs) need to cope with hazardous underwater medium using a limited computational capacity while facing unknown kinematics and disturbances. However, most algorithms proposed for navigation in such conditions fail to fulfil all conditions at the same time. In this work, we propose an optimal control method, based on a receding horizon approach, namely MPC (Model Predictive Control). Our model also estimates the kinematics of the medium and its disturbances, using efficient tools that rely on the use of linear algebra and first-order optimization methods. We also test our ideas using an extensive set of simulations, which show that the proposed ideas are very competitive in terms of cost and computational efficiency in cases of total and partial observability.

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Section: Discussionmentioning

confidence: 99%