Assessment of vision-based target detection and classification solutions using an indoor aerial robot
Ramos, Nicole R.
Chung, Timothy H.
Yakimenko, Oleg A.
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The role of unmanned aerial vehicles (UAVs) in military, commercial and recreational applications is continuously evolving as devel-opments in technology increase capabilities. The research herein presents an inexpensive computer-vision-based solution for detection and classification of a stationary target with a mobile aerial sensor as a prototyping platform. The main goal of this system is to use commercial-off-the-shelf and open-source components to reduce design complexity to provide a legacy product for future develop-ment of specific capabilities. Color imagery collected during flight using a low-resolution camera is used to test the application of a simple algorithm against a commercially available and low cost sensor. Original image processing algorithms that leverage the existing body of works in the open-source community are developed and tested within the Systems Engineering construct. System architec-ture leverages a modular approach that can be easily modified and adapted to changing requirements and objectives. Conclusions are drawn and recommendations for further study and system development are presented.