Work with the object detection model YOLO on NVIDIA Jetson Orin for real-time, on-board person detection.
Gain hands-on experience in fine-tuning pre-existing machine learning models for enhanced accuracy in person detection.
Be part of launching a fully operational in-flight detection system on our custom quadrotor platform.
Develop scripts that not only detect people but also report precise location data and relevant site characteristics.
Test and refine the system in diverse environmental conditions—sun, overcast, dusk—using a variety of camera systems.
Participate in live data acquisition during flight missions, helping to continuously improve the platform.
Track Composition:
Programming & Developing: 50% Flight Testing: 50%
Applications Closed
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Join our newly formed track on Autonomous Flight and Navigation.
Learn or enhance your skills in Linux, ROS2, Gazebo and RViz. for Autonomous Flight and Navigation on Drones.
Learn to understand intermediate concepts of navigation for drones in a simulated environment.
Test your trained skills in a series of three projects during the semester: – Developing simple projects for robotics with navigation using Gazebo. – Developing simple projects for UAV with navigation using Gazebo and PX4 – Develop an intermediate project for UAV with Computer Vision and SLAM.