UNMANNED AERIAL VEHICLE PAYLOAD OPTIMIZATION
Interdisciplinary Engineering Design Program
TEAM 15070 PROJECT SUMMARY
Class ENGR 498A/B
Sponsor UA Department of Electrical and Computer Engineering
Sponsor Mentor/Advisor Jonathan Sprinkle
Project Mentor Gary Redford
Team Members Hala Alzarkan Christian Adolfo Becerra Pierce Richard Simpson Jacob Ernest Vigil Adam Williams
(IE) (ECE) (ECE) (ME) (ECE)
IE = Industrial Engineering ECE = Electrical & Computer Engineering ME = Mechanical Engineering
This project involves the integration of software algorithms and autonomous unmanned aerial vehicles, or UAVs, used for unmanned missions. It was initiated as part of Microsoft’s Project Premonition to collect and analyze mosquitoes to look for early signs that potentially harmful diseases are spreading. The project is also part of the National Science Foundation’s Cyber-Physical Systems Virtual Organization. The goal of the project is to design and build a UAV-based hook system to capture and retrieve a mosquito trap. The design includes an electropermanent magnet, Pixhawk autopilot system, cameras, and sensors. The UAV has sufficient power and agility to carry the payload through a specified course, and an algorithm has been modified to allow the UAV to perform certain other tasks. The combination of the designed physical system and the modified algorithm will be used in a competition to navigate through an obstacle course.
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