Autonomous ground refuelling approach for civil aircrafts using computer vision and robotics

Simple item page
dc.contributor.authorYildirim, Suleyman
dc.contributor.authorRana, Zeeshan
dc.contributor.authorTang, Gilbert
dc.date.accessioned2022-01-17T16:45:00Z
dc.date.available2022-01-17T16:45:00Z
dc.date.issued2021-11-15
dc.description.abstract3D visual servoing systems need to detect the object and its pose in order to perform. As a result accurate, fast object detection and pose estimation play a vital role. Most visual servoing methods use low-level object detection and pose estimation algorithms. However, many approaches detect objects in 2D RGB sequences for servoing, which lacks reliability when estimating the object’s pose in 3D space. To cope with these problems, firstly, a joint feature extractor is employed to fuse the object’s 2D RGB image and 3D point cloud data. At this point, a novel method called PosEst is proposed to exploit the correlation between 2D and 3D features. Here are the results of the custom model using test data; precision: 0,9756, recall: 0.9876, F1 Score(beta=1): 0.9815, F1 Score(beta=2): 0.9779. The method used in this study can be easily implemented to 3D grasping and 3D tracking problems to make the solutions faster and more accurate. In a period where electric vehicles and autonomous systems are gradually becoming a part of our lives, this study offers a safer, more efficient and more comfortable environment.en_UK
dc.identifier.citationYildirim S, Rana Z, Tang G. (2021) Autonomous ground refuelling approach for civil aircrafts using computer vision and robotics. In: 2021 AIAA/IEEE 40th Digital Avionics Systems Conference (DASC), 3-7 October 2021, San Antonio, USAen_UK
dc.identifier.isbn978-1-6654-3421-8
dc.identifier.issn2155-7209
dc.identifier.urihttps://doi.org/10.1109/DASC52595.2021.9594312
dc.identifier.urihttps://dspace.lib.cranfield.ac.uk/handle/1826/17415
dc.language.isoenen_UK
dc.publisherIEEEen_UK
dc.rightsAttribution-NonCommercial 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by-nc/4.0/*
dc.subjectautonomousen_UK
dc.subjectaircraften_UK
dc.subjectrefuellingen_UK
dc.subjectroboticsen_UK
dc.subjectintegrationen_UK
dc.titleAutonomous ground refuelling approach for civil aircrafts using computer vision and roboticsen_UK
dc.typeConference paperen_UK

Files

Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
Autonomous_ground_refuelling_approach-civil_aircrafts-2021.pdf
Size:
2.23 MB
Format:
Adobe Portable Document Format
Description:
Download
License bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
1.63 KB
Format:
Item-specific license agreed upon to submission
Description:
Download

Collections

Staff publications (SATM)