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UAV Object Detection and Avoidance using Machine Learning – Phase 2 and Flight Demonstration

Company: Boeing

Major(s):
Primary: EE
Secondary: CMPEN
Optional: CMPSC, ME

Non-Disclosure Agreement: NO

Intellectual Property: NO

The aerospace environment is continuing to evolve with the introduction of unmanned aerial vehicles for package delivery and electric Vertical Takeoff and Landing air taxis to provide fast, efficient, and clean transportation within a local area. Boeing is also researching areas to implement autonomous solutions that further enhance the safety, predictability, and reliability of our products. This project will focus on a technology demonstration for a UAV that uses a camera-based object detection system to detect and avoid air-born obstacles. This project will be a continuation of a Spring 2023 project to further enhance the vision system, improve obstacle detection and range estimation, integrate obstacle avoidance capability into the flight control algorithms, and conduct a flight demonstration of the UAV capabilities as a complete system. Students interested in this awesome project: If you have experience with AI/ML, please indicate in the Optional comments section.

 
 

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