Towards Underwater Inspection Using AUVs

2015 ◽  
Vol 63 (5) ◽  
Author(s):  
Jörg Kalwa
Keyword(s):  
State Of The Art ◽  
Autonomous Underwater Vehicles ◽  
Underwater Vehicles ◽  
The State

AbstractAUVs – Autonomous Underwater Vehicles have reached a state of maturity that allows bringing them into applications beyond research. Still being a new “toy” in the toolbox for offshore work the market is somewhat reluctant to employ these robots due to missing field prove. This paper gives an overview about the state of the art of applications and technology and finalizes in a recent example, dmonstrating autonomy and robustness.

The Present and Future Capabilities of Deep ROVs

1999 ◽  
Vol 33 (4) ◽  
pp. 26-40 ◽  
Author(s):  
Robert Wernli
Keyword(s):  
State Of The Art ◽  
Autonomous Underwater Vehicles ◽  
Deep Ocean ◽  
Underwater Vehicles ◽  
The State ◽  
Remotely Operated Vehicles ◽  
Early Stages

The following paper will present an overview of Remotely Operated Vehicles (ROVs) and, in particular, their use in the deep ocean, which includes depths beyond 10,000 feet. Although the intent of the paper is to address tethered, free-flying vehicles, the categories of deep towed vehicles and autonomous underwater vehicles (AUVs) will also be included for completeness. And, to properly discuss the state-of-the-art in such deep ocean systems, their capabilities in the depths less than 10,000 ft will also be addressed. An attempt to project their uses in the early stages of the next millennium wiU also be made.

scholarly journals A Review of Visual-LiDAR Fusion based Simultaneous Localization and Mapping

Sensors ◽  
2020 ◽  
Vol 20 (7) ◽  
pp. 2068 ◽  
Author(s):  
César Debeunne ◽  
Damien Vivet
Keyword(s):  
Autonomous Navigation ◽  
Mobile Robotics ◽  
State Of The Art ◽  
Autonomous Underwater Vehicles ◽  
Simultaneous Localization And Mapping ◽  
Underwater Vehicles ◽  
Visual Features ◽  
Localization And Mapping ◽  
Comprehensive Survey ◽  
Self Driving Cars

Autonomous navigation requires both a precise and robust mapping and localization solution. In this context, Simultaneous Localization and Mapping (SLAM) is a very well-suited solution. SLAM is used for many applications including mobile robotics, self-driving cars, unmanned aerial vehicles, or autonomous underwater vehicles. In these domains, both visual and visual-IMU SLAM are well studied, and improvements are regularly proposed in the literature. However, LiDAR-SLAM techniques seem to be relatively the same as ten or twenty years ago. Moreover, few research works focus on vision-LiDAR approaches, whereas such a fusion would have many advantages. Indeed, hybridized solutions offer improvements in the performance of SLAM, especially with respect to aggressive motion, lack of light, or lack of visual features. This study provides a comprehensive survey on visual-LiDAR SLAM. After a summary of the basic idea of SLAM and its implementation, we give a complete review of the state-of-the-art of SLAM research, focusing on solutions using vision, LiDAR, and a sensor fusion of both modalities.

scholarly journals Multiple Receptive Field Network (MRF-Net) for Autonomous Underwater Vehicle Fishing Net Detection Using Forward-Looking Sonar Images

Sensors ◽  
2021 ◽  
Vol 21 (6) ◽  
pp. 1933
Author(s):  
Rixia Qin ◽  
Xiaohong Zhao ◽  
Wenbo Zhu ◽  
Qianqian Yang ◽  
Bo He ◽  
...  
Keyword(s):  
Receptive Field ◽  
Embedded System ◽  
Object Detection ◽  
Autonomous Underwater Vehicle ◽  
State Of The Art ◽  
Autonomous Underwater Vehicles ◽  
Underwater Vehicles ◽  
Field Network ◽  
Better Than ◽  
Forward Looking

Underwater fishing nets represent a danger faced by autonomous underwater vehicles (AUVs). To avoid irreparable damage to the AUV caused by fishing nets, the AUV needs to be able to identify and locate them autonomously and avoid them in advance. Whether the AUV can avoid fishing nets successfully depends on the accuracy and efficiency of detection. In this paper, we propose an object detection multiple receptive field network (MRF-Net), which is used to recognize and locate fishing nets using forward-looking sonar (FLS) images. The proposed architecture is a center-point-based detector, which uses a novel encoder-decoder structure to extract features and predict the center points and bounding box size. In addition, to reduce the interference of reverberation and speckle noises in the FLS image, we used a series of preprocessing operations to reduce the noises. We trained and tested the network with data collected in the sea using a Gemini 720i multi-beam forward-looking sonar and compared it with state-of-the-art networks for object detection. In order to further prove that our detector can be applied to the actual detection task, we also carried out the experiment of detecting and avoiding fishing nets in real-time in the sea with the embedded single board computer (SBC) module and the NVIDIA Jetson AGX Xavier embedded system of the AUV platform in our lab. The experimental results show that in terms of computational complexity, inference time, and prediction accuracy, MRF-Net is better than state-of-the-art networks. In addition, our fishing net avoidance experiment results indicate that the detection results of MRF-Net can support the accurate operation of the later obstacle avoidance algorithm.

Autonomous Underwater Vehicles for Ocean Research: Current Needs and State of the Art Technologies

2004 ◽  
Vol 38 (2) ◽  
pp. 63-72 ◽  
Author(s):  
Mark Sibenac ◽  
Tarun Podder ◽  
William Kirkwood ◽  
Hans Thomas
Keyword(s):  
State Of The Art ◽  
Autonomous Underwater Vehicles ◽  
Underwater Vehicles ◽  
Lessons Learned ◽  
Industrial Operations ◽  
History Of ◽  
Science Community ◽  
General Scientific ◽  
Science Application ◽  
The Military

Research in the field of scientific Autonomous Underwater Vehicles (AUVs) has been underway for over three decades. Much of the original work was funded by the military, and the vehicles were intended for Naval Ordnance Systems Command oceanographic needs, although the payloads were for general scientific use. Over the last decade, several autonomous underwater vehicles have been purpose built for both the science community and industrial operations around the world. Because of the variety of mission requirements, AUV configurations and options available today are numerous.Beginning with a brief overview of the history of AUVs for science, the paper continues with discussion of the ocean applications that are suitable to AUVs. Highlighted are some points a potential user might consider when selecting an AUV for a particular science application. An overview of several AUVs available today has been included exploring the cross-section of capabilities offered. This leads into the emerging requirements for AUVs of the future. In conclusion, some insight is given on lessons learned by several members of the oceanographic AUV community and how these lessons might be applicable when considering AUVs as a solution to today's intriguing oceanographic science questions.

Practical Picture Processing

1974 ◽  
Vol 32 ◽  
pp. 338-339
Author(s):  
T. A. Welton
Keyword(s):  
Radiation Damage ◽  
Coherence Length ◽  
Spatial Information ◽  
State Of The Art ◽  
Coherent Radiation ◽  
The State ◽  
Energy Spread ◽  
Electron Micrograph ◽  
Picture Processing ◽  
Molecular Skeleton

Various authors have emphasized the spatial information resident in an electron micrograph taken with adequately coherent radiation. In view of the completion of at least one such instrument, this opportunity is taken to summarize the state of the art of processing such micrographs. We use the usual symbols for the aberration coefficients, and supplement these with £ and 6 for the transverse coherence length and the fractional energy spread respectively. He also assume a weak, biologically interesting sample, with principal interest lying in the molecular skeleton remaining after obvious hydrogen loss and other radiation damage has occurred.

Hypothesis-Evidence Coordination: The State of the Art

2003 ◽  
Vol 48 (6) ◽  
pp. 826-829 ◽  
Author(s):  
Eric Amsel
Keyword(s):  
State Of The Art ◽  
The State

The State of the Art

1968 ◽  
Vol 13 (9) ◽  
pp. 479-480
Author(s):  
LEWIS PETRINOVICH
Keyword(s):  
State Of The Art ◽  
The State

Needs Assessment: The State of the Art

1984 ◽  
Vol 29 (5) ◽  
pp. 426-428
Author(s):  
Anthony R. D'Augelli
Keyword(s):  
Needs Assessment ◽  
State Of The Art ◽  
The State
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