Distributed Adaptive Neural Network Control Applied to a Formation Tracking of a Group of Low-Cost Underwater Drones in Hazardous Environments

Hoang Anh Pham,Thierry Soriano,Valentin Gies,Van Hien Ngo

doi:10.3390/app10051732

Hoang Anh Pham, Thierry Soriano + Show 2 more

Open Access

https://doi.org/10.3390/app10051732

Copy DOI

Abstract

This paper addresses a formation tracking problem of multiple low-cost underwater drones by implementing distributed adaptive neural network control (DANNC). It is based on a leader-follower architecture to operate in hazardous environments. First, unknown parameters of underwater vehicle dynamics, which are important requirements for real-world applications, are approximated by a neural network using a radial basis function. More specifically, those parameters are only calculated by local information, which can be obtained by an on-board camera without using an external positioning system. Secondly, a potential function is employed to ensure there is no collision between the underwater drones. We then propose a desired configuration of a group of unmanned underwater vehicles (UUVs) as a time-variant function so that they can quickly change their shape between them to facilitate the crossing in a narrow area. Finally, three UUVs, based on a robot operating system (ROS) platform, are used to emphasize the realistic low-cost aspect of underwater drones. The proposed approach is validated by evaluating in different experimental scenarios.

Highlights

In recent years, the application of unmanned underwater vehicles (UUVs) has grown steadily.Several activities related to the offshore industry, such as oceanic surveillance, undersea oil detections, seabed explorations, and so on, have been performed by using a group of low-cost, unmanned, small underwater vehicles
The formation tracking control problems of a group of low-cost underwater drones are subject to nonlinearity, parametric uncertainties, and external disturbances have been discussed and implemented
A complete scenario of the underwater drone operation has been simulated by integrating the formation tracking control term and the collision-obstacle avoidance term

Summary

Introduction

Several activities related to the offshore industry, such as oceanic surveillance, undersea oil detections, seabed explorations, and so on, have been performed by using a group of low-cost, unmanned, small underwater vehicles. Its advantages are it is an effective, economic, and efficient solution, compared to a single expensive underwater vehicle. An essential topic in the cooperative control of multi-UUVs is the formation tracking problem [1,2,3].

Objectives

Results

Conclusion