A Co-Operative Autonomous Offshore System for Target Detection Using Multi-Sensor Technology

Jose Villa,Kari T Koskinen,Sauli Virta,Jussi Aaltonen

doi:10.3390/rs12244106

Abstract

This article studies the design, modeling, and implementation challenges for a target detection algorithm using multi-sensor technology of a co-operative autonomous offshore system, formed by an unmanned surface vehicle (USV) and an autonomous underwater vehicle (AUV). First, the study develops an accurate mathematical model of the USV to be included as a simulation environment for testing the guidance, navigation, and control (GNC) algorithm. Then, a guidance system is addressed based on an underwater coverage path for the AUV, which uses a mechanical imaging sonar as the primary AUV perception sensor and ultra-short baseline (USBL) as a positioning system. Once the target is detected, the AUV sends its location to the USV, which creates a straight-line for path following with obstacle avoidance capabilities, using a LiDAR as the main USV perception sensor. This communication in the co-operative autonomous offshore system includes a decentralized Robot Operating System (ROS) framework with a master node at each vehicle. Additionally, each vehicle uses a modular approach for the GNC architecture, including target detection, path-following, and guidance control modules. Finally, implementation challenges in a field test scenario involving both AUV and USV are addressed to validate the target detection algorithm.

Highlights

In recent years, the use of autonomous offshore vehicles, which includes autonomous underwater vehicles (AUVs) and unmanned surface vehicles (USVs), for marine interventions has attracted increasing interest from research scientists, maritime industries, and the military
The experimental results of this study are shown in a modular way, testing each of the subsystems separately to validate the target detection algorithm using multi-sensor technology
Regarding the USV field test, it is demonstrated in a clear obstacle area at the lake

Summary

Introduction

The use of autonomous offshore vehicles, which includes autonomous underwater vehicles (AUVs) and unmanned surface vehicles (USVs), for marine interventions has attracted increasing interest from research scientists, maritime industries, and the military. These interventions include several activities such as offshore surveillance, offshore target detection, seabed explorations, or search and rescue (SAR) missions. In [2], the study used a heterogeneous collaborative system of above, surface, and underwater robots to obtain a multi-domain awareness on a floating target. In [4], the control scenario simulated a homogeneous AUV fleet to study formation tracking control and collision-obstacle avoidance

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Results

Conclusion