scholarly journals The AEROARMS Project: Aerial Robots with Advanced Manipulation Capabilities for Inspection and Maintenance

2018 ◽  
Vol 25 (4) ◽  
pp. 12-23 ◽  
Author(s):  
Anibal Ollero ◽  
Juan Cortes ◽  
Angel Santamaria-Navarro ◽  
Miguel Angel Trujillo Soto ◽  
Ribin Balachandran ◽  
...  
Keyword(s):  
Aerial Robots ◽  
Inspection And Maintenance

scholarly journals Safe Local Aerial Manipulation for the Installation of Devices on Power Lines: AERIAL-CORE First Year Results and Designs

2021 ◽  
Vol 11 (13) ◽  
pp. 6220
Author(s):  
Jonathan Cacace ◽  
Santos M. Orozco-Soto ◽  
Alejandro Suarez ◽  
Alvaro Caballero ◽  
Matko Orsag ◽  
...  
Keyword(s):  
Power Lines ◽  
First Year ◽  
Heavy Vehicles ◽  
Aerial Manipulation ◽  
Bird Flight ◽  
Aerial Robots ◽  
Periodic Inspection ◽  
Inspection And Maintenance ◽  
Human Operators ◽  
Core Project

The power grid is an essential infrastructure in any country, comprising thousands of kilometers of power lines that require periodic inspection and maintenance, carried out nowadays by human operators in risky conditions. To increase safety and reduce time and cost with respect to conventional solutions involving manned helicopters and heavy vehicles, the AERIAL-CORE project proposes the development of aerial robots capable of performing aerial manipulation operations to assist human operators in power lines inspection and maintenance, allowing the installation of devices, such as bird flight diverters or electrical spacers, and the fast delivery and retrieval of tools. This manuscript describes the goals and functionalities to be developed for safe local aerial manipulation, presenting the preliminary designs and experimental results obtained in the first year of the project.

Unlocking Oil Resources without Artificial Lift Using Testing Barge in Tambora Gas Field

2020 ◽  
Author(s):  
J., A. Anggoro
Keyword(s):  
Oil Recovery ◽  
Gas Field ◽  
Artificial Lift ◽  
Oil Resources ◽  
Cumulative Production ◽  
Inspection And Maintenance ◽  
Routine Inspection ◽  
Prime Condition ◽  
Safety Operation ◽  
Mahakam Delta

Tambora field is a mature gas field located in a swamp area of Mahakam delta without artificial lift. The main objective of this project is to unlock existing oil resources. Most oil wells could not flow because there is no artificial lift, moreover the network pressure is still at Medium Pressure (20 Barg). Given the significant stakes, the option to operate the testing barge continuously as lifting tool is reviewed. The idea is to set the separator pressure to 1-3 Barg, so that the wellhead flowing pressure could be reduced to more than 15 Barg which will create higher drawdown in front of the reservoir. The oil flows from the reservoir into the gauge tank, where it is then returned to the production line by transfer pumps. The trial was performed in well T-1 for a week in November 2017 and successfully produced continuous oil with a stable rate of 1000 bbls/d. What makes this project unique is the continuous operation for a long period of time. Therefore, it is important to ensure the capacity of the gauge tank and the transfer pump compatibility with the rate from the well, the system durability which required routine inspection and maintenance to ensure the testing barge unit is in prime condition and to maintain vigilance and responsiveness of personnel. This project started in 2018 for several wells and the cumulative production up to January 2020 has reached 158 k bbls and will be continued as there are still potential oil resources to be unlocked. Innovation does not need to be rocket science. Significant oil recovery can be achieved with a simple approach considering all safety operation, production and economic aspect.

Inspection and Maintenance Management for Concrete Bridges at JR East

2018 ◽  
Vol 56 (1) ◽  
pp. 40-44
Author(s):  
M. Hirota ◽  
M. Tomori ◽  
D. Tsukishima
Keyword(s):  
Concrete Bridges ◽  
Maintenance Management ◽  
Inspection And Maintenance

scholarly journals Fig Plant Segmentation from Aerial Images Using a Deep Convolutional Encoder-Decoder Network

2019 ◽  
Vol 11 (10) ◽  
pp. 1157 ◽  
Author(s):  
Jorge Fuentes-Pacheco ◽  
Juan Torres-Olivares ◽  
Edgar Roman-Rangel ◽  
Salvador Cervantes ◽  
Porfirio Juarez-Lopez ◽  
...  
Keyword(s):  
Precision Agriculture ◽  
Image Data ◽  
Ground Truth ◽  
Aerial Images ◽  
Aerial Image ◽  
Data Set ◽  
Visual Appearance ◽  
Aerial Robots ◽  
Lighting Conditions ◽  
Convolutional Encoder

Crop segmentation is an important task in Precision Agriculture, where the use of aerial robots with an on-board camera has contributed to the development of new solution alternatives. We address the problem of fig plant segmentation in top-view RGB (Red-Green-Blue) images of a crop grown under open-field difficult circumstances of complex lighting conditions and non-ideal crop maintenance practices defined by local farmers. We present a Convolutional Neural Network (CNN) with an encoder-decoder architecture that classifies each pixel as crop or non-crop using only raw colour images as input. Our approach achieves a mean accuracy of 93.85% despite the complexity of the background and a highly variable visual appearance of the leaves. We make available our CNN code to the research community, as well as the aerial image data set and a hand-made ground truth segmentation with pixel precision to facilitate the comparison among different algorithms.

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