An Improved Localization Method for the Transition between Autonomous Underwater Vehicle Homing and Docking.

Ri Lin,Gengli Zhou,Dejun Li,Mingwei Lin,Feng Zhang,Canjun Yang

doi:10.3390/s21072468

Abstract

Docking technology for autonomous underwater vehicles (AUVs) involves energy supply, data exchange and navigation, and plays an important role to extend the endurance of the AUVs. The navigation method used in the transition between AUV homing and docking influences subsequent tasks. How to improve the accuracy of the navigation in this stage is important. However, when using ultra-short baseline (USBL), outliers and slow localization updating rates could possibly cause localization errors. Optical navigation methods using underwater lights and cameras are easily affected by the ambient light. All these may reduce the rate of successful docking. In this paper, research on an improved localization method based on multi-sensor information fusion is carried out. To improve the localization performance of AUVs under motion mutation and light variation conditions, an improved underwater simultaneous localization and mapping algorithm based on ORB features (IU-ORBSALM) is proposed. A nonlinear optimization method is proposed to optimize the scale of monocular visual odometry in IU-ORBSLAM and the AUV pose. Localization tests and five docking missions are executed in a swimming pool. The localization results indicate that the localization accuracy and update rate are both improved. The 100% successful docking rate achieved verifies the feasibility of the proposed localization method.

Highlights

Due to its characteristics of high pressure, electromagnetic wave shielding and complex topography, it is a great challenge to explore and develop the ocean
Since the development of underwater vehicles, the navigation methods can be roughly divided into three categories [6]: geophysical navigation methods, dead reckoning or multi-data coupling navigation methods and navigation methods based on acoustic sensors
The pose of the autonomous underwater vehicles (AUVs) and the scale coefficient of monocular visual odometry are changes can only be obtained from two adjacent frames, which leads to cumulative error simultaneously taken as variables to be optimized

Summary

Introduction

Due to its characteristics of high pressure, electromagnetic wave shielding and complex topography, it is a great challenge to explore and develop the ocean. Among them, cabled ocean observation networks (COONs) and autonomous underwater vehicles (AUVs) are the most well-known of these observation methods. The AUV which carries own energy system and various detection sensors can navigate autonomously to execute observation missions. In order to combine the above two observation methods, underwater docking technology is proposed which effectively extends the observation time and range of the AUVs [2,3,4,5]. Since the development of underwater vehicles, the navigation methods can be roughly divided into three categories [6]: geophysical navigation methods, dead reckoning or multi-data coupling navigation methods and navigation methods based on acoustic sensors. For AUVs, the most commonly used navigation method is dead reckoning or multi-data coupling navigation [7,8]. The acoustic navigation commonly uses an ultra-short baseline (USBL)

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Results