Real-time image processing in a multi-UAV system for structural surveillance through IoT platform

Jose Falcon; Mehrube Mehrubeoglu; Pablo Rangel

doi:10.1117/12.2622362

27 May 2022 Real-time image processing in a multi-UAV system for structural surveillance through IoT platform

Jose Falcon, Mehrube Mehrubeoglu, Pablo Rangel

Proceedings Volume 12102, Real-Time Image Processing and Deep Learning 2022; 121020F (2022) https://doi.org/10.1117/12.2622362
Event: SPIE Defense + Commercial Sensing, 2022, Orlando, Florida, United States

Abstract

The use of location and instruction markers for multi-path planning enhancement in any set of unmanned aerial systems’ tasks is crucial to the coordination and effectiveness of the individual unmanned aerial vehicles (UAVs). This research implements OpenCV algorithms that allow multiple UAVs to use ArUco markers to receive data related to location and instruction for the purposes of multi-path planning. OpenCV algorithms are utilized to develop vision-based solutions that will enhance the real-time capabilities of the UAVs. The final goal for the multi-drone system entails inspecting and surveying objects for structural damage and applying the developed image processing algorithms to collected images to determine the significance of damage. This project utilizes OpenCV and Python libraries for multi-drone pathway planning by collecting, transmitting, and displaying real-world industrially valuable data over the network infrastructure as an application of Internet of Things (IoT).

Conference Presentation

Citation Download Citation

Jose Falcon, Mehrube Mehrubeoglu, and Pablo Rangel "Real-time image processing in a multi-UAV system for structural surveillance through IoT platform", Proc. SPIE 12102, Real-Time Image Processing and Deep Learning 2022, 121020F (27 May 2022); https://doi.org/10.1117/12.2622362

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