Optimising the Computer Vision Module of Eonics’ Autonomous Drone

Title

Optimising the Computer Vision Module of Eonics’ Autonomous Drone

 Author

Yarally, Tim (TU Delft Electrical Engineering, Mathematics and Computer Science)
van Willegen, Toby (TU Delft Electrical Engineering, Mathematics and Computer Science)
Brinkhuis, Mees (TU Delft Electrical Engineering, Mathematics and Computer Science)
den Hoedt, Dirk (TU Delft Electrical Engineering, Mathematics and Computer Science)
van der Meer, Mike (TU Delft Electrical Engineering, Mathematics and Computer Science)

Contributor

Urbano Merino, J. (mentor)
Visser, Otto (graduation committee)
Overklift Vaupel Klein, Thomas (graduation committee)

Degree granting institution

Delft University of Technology

 Date

2020-02-06

 Abstract

Items being misplaced in warehouses easily get lost. To combat this, warehouses have to send people in scanning all barcodes in the warehouse. This is highly inefficient, which is why Eonics wants to build a drone handling this. There are options out there to scan barcodes, but none of them match the requirements laid out by Eonics. Among these requirements are a lightweight camera, such as a GoPro, and a recording distance of 1.5-2 metres. This report will look and see if these requirements are feasible. Techniques used in this report are Mathematical Morphology, Maximally Stable Extremal Regions, Convolutional Neural Networks, Gradiental Difference and Direction Estimation with Region Extraction. The report concludes in stating that interpreting the barcodes is not possible with mere software under these requirements. The maximal distance we were able to interpret barcodes from, based on a 4K image, was around 1 metre. Continuing the trend, we would need at least an 8K camera to detect from a distance of 1.5 metres. Detection however, is less difficult and is feasible from a distance of 1.5-2 metres. The report also derives an function to use to calculate the maximum distance a barcode can be interpreted from, based on the details of the barcode and camera. Finally, research is done regarding using hardware solutions, such as a zoom-lens, which has promising results.

 Subject

barcode
Barcode localization

 To reference this document use:

http://resolver.tudelft.nl/uuid:caa6b17a-b94f-471c-aa22-985587f71416

 Part of collection

Student theses

 Document type

bachelor thesis

 Rights

© 2020 Tim Yarally, Toby van Willegen, Mees Brinkhuis, Dirk den Hoedt, Mike van der Meer
Files
PDF Eonics_Drone_Final_Paper_1_.pdf 17.09 MB
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