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KESTREL

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Autonomous Videography Drone

KESTREL
UltralyticsC++PytorchROSPythonUbuntuGithubMongodbReactNode.jsExpressJavascript

Project Description

An autonomous drone project leveraging modern robotics, computer vision, and embedded systems to achieve intelligent flight and person-tracking capabilities using a modular ROS 2 stack and on-board edge AI computing.

Sponsor

Blue Origin

Tech Stack: Ultralytics • C++ • Pytorch • ROS • Python • Ubuntu • Github • Mongodb • React • Node.js • Express • Javascript

Soft Skills: Leadership • Team Leadership • Adaptability • Change Management • Collaboration • Conflict Resolution • Prioritization • Vision Setting • Workflow Design • Team Building

Development Timeline

These test flights showcased the DeepSORT system for object tracking, the obstacle avoidance system and flight pathing system, and finally the base station communication. Everything was successful and showed a promising wrap-up for the project.

As I began my capstone project, VITALS, I chose to hand off the project to ACM and the leadership I put in position to continue the implementation of the research and continue working towards test flights and wrapping up the project.

Moving into the summer of 2025, the project underwent restructuring within the leadership and the structure of the club support. Before 2025, we were mainly supported by the ACM club as well as other smaller clubs. With the help of some dedicated members within ACM, we were able to acquire a partnership within the IEEE club at UCF, acquiring many skilled Electrical and Computer Engineers to help advance the project in aspects that were lacking.

Applied for Blue Origin Technical Project Sponsorship and was rewarded a 1000 dollar sponsorship as well as technical mentorship to help advance the project forward.

This was the first meeting for Project Kestrel. This Meeting was held through the Association for Computing Machinery (ACM) club at UCF, as well as publicized through the AI@UCF club, and later on partnered with several other clubs. In this meeting, we reviewed TensorFlow's introductory YouTube videos on how CNN's work and provided a simple introduction to the project's goal, vision, and timeline.