Spatial Visualization Based on Geodata Fusion Using an Autonomous Unmanned Vessel

Abstract

The visualization of riverbeds and surface facilities on the banks is crucial for systems that analyze conditions, safety, and changes in this environment. Hence, in this paper, we propose collecting, and processing data from a variety of sensors—sonar, LiDAR, multibeam echosounder (MBES), and camera—to create a visualization for further analysis. For this purpose, we took measurements from sensors installed on an autonomous, unmanned hydrographic vessel, and then proposed a data fusion mechanism, to create a visualization using modules under and above the water. A fusion contains key-point analysis on classic images and sonars, augmentation/reduction of point clouds, fitting data and mesh creation. Then, we also propose an analysis module that can be used to compare and extract information from created visualizations. The analysis module is based on artificial intelligence tools for the classification tasks, which helps in further comparison to archival data. Such a model was tested using various techniques to achieve the fastest and most accurate visualizations possible in simulation and real case studies.

Testing and Analysis of Selected Navigation Parameters of the GNSS/INS System for USV Path Localization during Inland Hydrographic Surveys

“…Two GNSS antennas were mounted on the mast of the USV, which were approx. 2 m apart ( Figure 1 ) [ 4 , 8 , 12 ].…”

“…An Unmanned Surface Vehicle (USV) is a surface vehicle that can move on the water surface without the need of a crew on board [ 1 , 2 ]. USVs are remotely controlled or can operate in autonomous mode, using various sensors, communication and control systems, as well as navigation technologies [ 3 , 4 ]. Unmanned vessels have many advantages such as the ability to carry out long-term missions, work in hard-to-reach places, reduce risk for the crew and the ability to collect large amounts of data [ 5 , 6 , 7 ] using various sensors such as cameras, echosounders, RAdio Detection AND Ranging (RADAR), Light Detection And Ranging (LiDAR), Inertial Navigation System (INS), Global Navigation Satellite System (GNSS), sonars, etc.…”

“…Two GNSS antennas were mounted on the mast of the USV, which were approx. 2 m apart (Figure 1) [4,8,12]. The IMU was mounted near the symmetry axis of the "HydroDron" USV.…”

Advanced Marine Craft Model Identification via Multi-Kernel Weighted Least Square Support Vector Machine and Characteristic Model Techniques

“…To better perform these tasks in oceanic environments, it is increasingly important to master hydrodynamics models of marine crafts and predict their maneuverability. Besides, the geodata fusion [6] and side scan sonar analysis [7] for the Internet of Things field have also been successfully implemented based on marine crafts. Geodata fusion combines data from various sources, including satellite imagery and remote sensors, to create an integrated and accurate picture of the marine environment.…”