Computer Vision Based Detect and Avoid on UAV Platforms

This project led to the development of a detection and localization algorithm of multiple aircraft in a video sequence via supervised machine learning techniques. The algorithm detects aircraft in a video frame, classifies the aircraft to get an estimate of its size, and then estimates its position in the real world as an offset from the position of the camera. The project also conducted an evaluation of user interface design with regard to reaction to obstacles detected from a LEDDAR/Radar/Camera system.

Further work was done towards development and comparison of detect and avoid alogirthms for UAVV platforms via rienforcement learning techniques in order to improve the method to account for various avoidance strategies.

Role: Lead graduate researcher.