scholarly journals MULTI-CAMERA SYSTEM CALIBRATION OF A LOW-COST REMOTELY OPERATED VEHICLE FOR UNDERWATER CAVE EXPLORATION

2018 ◽  
Vol XLII-1 ◽  
pp. 329-337 ◽  
Author(s):  
E. Nocerino ◽  
M. M. Nawaf ◽  
M. Saccone ◽  
M. B. Ellefi ◽  
J. Pasquet ◽  
...  
Keyword(s):  
Autonomous Navigation ◽  
Low Cost ◽  
Technological Advancement ◽  
Remotely Operated Vehicle ◽  
Science And Engineering ◽  
Camera System ◽  
Confined Spaces ◽  
Underwater Environment ◽  
Localization And Mapping ◽  
Underwater Exploration

<p><strong>Abstract.</strong> Exploration, documentation and mapping of underwater environment is one of the biggest open challenges for science and engineering. Humankind is not naturally designed to operate in water and, despite the enormous technological advancement that offers nowadays unprecedented opportunities, diving and working underwater is still very dangerous, especially in confined spaces such as underwater caves. Great research efforts are currently devoted to underwater autonomous navigation, but available solutions still mainly rely on complex and expensive systems, due to the difficulty of adapting localization and mapping sensors and algorithms suited for terrestrial or aerial applications. However, small and affordable underwater remotely operated vehicles (ROVs) are available, which offer good opportunities for underwater exploration and mapping. This paper focuses on the development of a small, low-cost ROV designed for 3D mapping of underwater environments, like caves. The system is based on a commercially available vehicle, the BluRov2, and relies on the use of up to 12 action cameras (GoPro) mounted on it. A trifocal camera system for underwater real-time visual odometry can also be included. The work describes the photogrammetric procedure developed for the synchronization and calibration of the GoPro cameras and provides a thorough analysis on the achievable results.</p>

scholarly journals The Development of a Low Cost Inertial Navigation System for a Remotely Operated Vehicle

2021 ◽  
Author(s):  
◽  
Jason Dean Edwards
Keyword(s):  
Navigation System ◽  
Inertial Navigation System ◽  
Low Cost ◽  
Inertial Navigation ◽  
Electronic Systems ◽  
Remotely Operated Vehicle ◽  
Underwater Environment ◽  
Laser Scanners ◽  
System Use ◽  
Robotic Vehicles

<p>Modern robotic vehicles use a large and varied set of sensors to navigate and localise their position in the environment and determine where they should be heading to accomplish their tasks. These sensors include GPS, infrared and ultrasonic range finders, laser scanners and sonar. However, the underwater environment presents challengers for modern robotic vehicles because most sensors that are typically used for navigation and localisation have reduced or no functionality underwater. This thesis details the design and construction of a low cost Inertial Navigation System use on the Victoria University of Wellington's (VUW) Mechatronics group Remotely Operated Vehicle (ROV). The major electronic systems, comprising of the onboard computer and microcontroller, of the ROV have been upgraded to allow for the increased computational power that the Inertial Navigation System needs and to allow further upgrading and installation of electrical and electronic systems in the vehicle as they are required. Modifications to the chassis allow quick and simple disassembly of the ROV to repair or replace major components if the need arises.</p>

scholarly journals Comparison between low-cost passive and active vision for obstacle depth

2020 ◽  
Vol 6 ◽  
Author(s):  
Thiago Rateke ◽  
Vito Francisco Chiarella ◽  
Karla Aparecida Justen ◽  
Antonio Carlos Sobieranski ◽  
Sylvio Luiz Mantelli Neto ◽  
...  
Keyword(s):  
Autonomous Navigation ◽  
Low Cost ◽  
Active Vision ◽  
Obstacle Detection ◽  
Disparity Map ◽  
Driver Assistance ◽  
Driver Assistance Systems ◽  
Passive Devices ◽  
Localization And Mapping ◽  
Better Than

Obstacle detection is a key issue in many current applications, especially in applications that have been increasingly highlighted such as: advanced driver assistance systems (ADAS), simultaneous localization and mapping (SLAM) and autonomous navigation system. This can be achieved by active and passive acquisition vision systems, for example: laser and cameras respectively. In this paper we present a comparison between low-cost active and passive devices, more specifically LIDAR and two cameras. To this comparison a disparity map is created by stereo correspondence through two images and a point cloud map created by LIDAR data values (distances measures). The obtained results shown that passive vision can be as good as or even better than active vision in low cost scenarios.

scholarly journals AQUALOC: An underwater dataset for visual–inertial–pressure localization

2019 ◽  
Vol 38 (14) ◽  
pp. 1549-1559 ◽  
Author(s):  
Maxime Ferrera ◽  
Vincent Creuze ◽  
Julien Moras ◽  
Pauline Trouvé-Peloux
Keyword(s):  
Inertial Measurement Unit ◽  
Low Cost ◽  
Underwater Vehicles ◽  
Measurement Unit ◽  
Inertial Measurement ◽  
Computing Unit ◽  
Underwater Environment ◽  
Localization And Mapping ◽  
Vision Based Localization ◽  
Archeological Site

We present a new dataset, dedicated to the development of simultaneous localization and mapping methods for underwater vehicles navigating close to the seabed. The data sequences composing this dataset are recorded in three different environments: a harbor at a depth of a few meters, a first archeological site at a depth of 270 meters, and a second site at a depth of 380 meters. The data acquisition is performed using remotely operated vehicles equipped with a monocular monochromatic camera, a low-cost inertial measurement unit, a pressure sensor, and a computing unit, all embedded in a single enclosure. The sensors’ measurements are recorded synchronously on the computing unit and 17 sequences have been created from all the acquired data. These sequences are made available in the form of ROS bags and as raw data. For each sequence, a trajectory has also been computed offline using a structure-from-motion library in order to allow the comparison with real-time localization methods. With the release of this dataset, we wish to provide data difficult to acquire and to encourage the development of vision-based localization methods dedicated to the underwater environment. The dataset can be downloaded from: http://www.lirmm.fr/aqualoc/

scholarly journals The Development of a Low Cost Inertial Navigation System for a Remotely Operated Vehicle

2021 ◽  
Author(s):  
◽  
Jason Dean Edwards
Keyword(s):  
Navigation System ◽  
Inertial Navigation System ◽  
Low Cost ◽  
Inertial Navigation ◽  
Electronic Systems ◽  
Remotely Operated Vehicle ◽  
Underwater Environment ◽  
Laser Scanners ◽  
System Use ◽  
Robotic Vehicles

<p>Modern robotic vehicles use a large and varied set of sensors to navigate and localise their position in the environment and determine where they should be heading to accomplish their tasks. These sensors include GPS, infrared and ultrasonic range finders, laser scanners and sonar. However, the underwater environment presents challengers for modern robotic vehicles because most sensors that are typically used for navigation and localisation have reduced or no functionality underwater. This thesis details the design and construction of a low cost Inertial Navigation System use on the Victoria University of Wellington's (VUW) Mechatronics group Remotely Operated Vehicle (ROV). The major electronic systems, comprising of the onboard computer and microcontroller, of the ROV have been upgraded to allow for the increased computational power that the Inertial Navigation System needs and to allow further upgrading and installation of electrical and electronic systems in the vehicle as they are required. Modifications to the chassis allow quick and simple disassembly of the ROV to repair or replace major components if the need arises.</p>

scholarly journals LOCALIZATION AND MAPPING USING A NON-CENTRAL CATADIOPTRIC CAMERA SYSTEM

2018 ◽  
Vol IV-2 ◽  
pp. 145-152
Author(s):  
M. Khurana ◽  
C. Armenakis
Keyword(s):  
Low Cost ◽  
Calibration Method ◽  
Indoor Navigation ◽  
Field Of View ◽  
Wide Field ◽  
Camera System ◽  
Cost System ◽  
Localization And Mapping ◽  
Camera Localization ◽  
Catadioptric Camera

This work details the development of an indoor navigation and mapping system using a non-central catadioptric omnidirectional camera and its implementation for mobile applications. Omnidirectional catadioptric cameras find their use in navigation and mapping of robotic platforms, owing to their wide field of view. Having a wider field of view, or rather a potential 360&amp;deg; field of view, allows the system to “see and move” more freely in the navigation space. A catadioptric camera system is a low cost system which consists of a mirror and a camera. Any perspective camera can be used. A platform was constructed in order to combine the mirror and a camera to build a catadioptric system. A calibration method was developed in order to obtain the relative position and orientation between the two components so that they can be considered as one monolithic system. The mathematical model for localizing the system was determined using conditions based on the reflective properties of the mirror. The obtained platform positions were then used to map the environment using epipolar geometry. Experiments were performed to test the mathematical models and the achieved location and mapping accuracies of the system. An iterative process of positioning and mapping was applied to determine object coordinates of an indoor environment while navigating the mobile platform. Camera localization and 3D coordinates of object points obtained decimetre level accuracies.

scholarly journals A V-SLAM Guided and Portable System for Photogrammetric Applications

2021 ◽  
Vol 13 (12) ◽  
pp. 2351
Author(s):  
Alessandro Torresani ◽  
Fabio Menna ◽  
Roberto Battisti ◽  
Fabio Remondino
Keyword(s):  
Low Cost ◽  
Cost Effective ◽  
Motion Blur ◽  
Guidance System ◽  
Prototype System ◽  
Active Sensors ◽  
Localization And Mapping ◽  
Acquisition Speed ◽  
Mobile Mapping System ◽  
Slam Algorithm

Mobile and handheld mapping systems are becoming widely used nowadays as fast and cost-effective data acquisition systems for 3D reconstruction purposes. While most of the research and commercial systems are based on active sensors, solutions employing only cameras and photogrammetry are attracting more and more interest due to their significantly minor costs, size and power consumption. In this work we propose an ARM-based, low-cost and lightweight stereo vision mobile mapping system based on a Visual Simultaneous Localization And Mapping (V-SLAM) algorithm. The prototype system, named GuPho (Guided Photogrammetric System) also integrates an in-house guidance system which enables optimized image acquisitions, robust management of the cameras and feedback on positioning and acquisition speed. The presented results show the effectiveness of the developed prototype in mapping large scenarios, enabling motion blur prevention, robust camera exposure control and achieving accurate 3D results.

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