A semi-autonomous flight and object recognition program was explored by two undergraduate researchers to navigate the 2022 DASC Drone Competition course and detect ground-based yellow rubber ducks utilizing a Tello EDU μdrone Unmanned Aerial System (UAS). The research team used several programs and libraries to accomplish the aforementioned tasks namely: Python and OpenCV-Python. Initially, the research team did not succeed in developing a fully autonomous flight and object detection program due to hardware limitations within the microdrone. After several engineering iterations, the research team was able to achieve consistent successful semi-autonomous flight and object detection using the UAS and associated personal hardware.


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    Title :

    Development of Semi-Autonomous Flight & Detection Systems Using Small Drones


    Contributors:


    Publication date :

    2022-09-18


    Size :

    1930794 byte





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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