NXP HoverGames 2 Winners Demonstrate Innovative Drones Solutions To Help With Pandemics


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In the HoverGames 2 Challenge, “Helping Drones, Helping Others during Epidemics,” we asked contestants to devise innovative ways for drones to help people in need, improve crisis management or even directly prevent the spread of disease. We’re glad to tell you that the talented contestants have put their creativity to the test and come up with compelling drone solutions to help. Participants were asked to build and test their idea with the NXP full robotic drone kit and integrate the “NavQ” pilot sight system and mission computer based on the NXP i.MX 8M Mini. They were asked to share the code so that their ideas could also inspire others and literally “help others”. Winning entries Food shortages were a real threat during the pandemic. Many of us remember empty shelves of pasta, flour, yeast, and even powdered sugar. Due to closed borders, harvest workers were initially unable to enter many countries. Farmers lacked the manpower to harvest and manage their crops. First Place Team SCAREcrow solution that enables maintaining guarding via aerial reconnaissance and escort This system, which sits passively in the farmer’s field, monitors animal intruders, and sends out an NXP drone to scare off potential threats, can be easily expanded for coordinated control of multiple drones With multiple agents to cover larger isolation areas more effectively. This idea applies neural networks with augmented learning and shows a new and innovative use case for drones in agriculture. SCAREcrow, 2nd place, Dobrea Dan Marius drone to preserve quarantine area Dobrea’s idea focuses on an autonomous drone to maintain and support quarantine areas. As a starting point, Dobrea built a development system based on HoverGames unmanned aerial vehicles, a robotic unmanned flight management module, and a companion computer for Linux. Using the PX4 autopilot NXP FMUK66, the drone will make a pre-programmed autonomous flight around the quarantine area and back to the landing point. If movement is detected via the smart system, the drone will send an update to the base station. The system can also support various kinds of applications such as cargo transportation. Drone Fabian Piccardo is in third place to save mental health The drone uses object detection and tracking algorithms using OpenCV to monitor pedestrians and upload the combined path that has been ported to the mapping app. The map shows a 4-meter 3-D bubble of the treadmill that can help others make precise movements when they decide to go out. Since the camera Fabio used turned out to be too heavy for a drone, he printed a basic mechanism that could support dampers and handle both the NavQ board and the Coral camera to provide space for the flight controller in the center of the drone. Conclusion We are pleased with the large number of high-quality submissions: it was extremely difficult to judge the top three and a tight race among all the highest-ranked entries. Thank you all for their great contributions, collaborative online discussions, great videos, and sharing. Read the full article at NXP.


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