Autonomous Rogue Drone Capture Research
Developing an autonomous drone system that uses computer vision, target prediction, and a net-based capture mechanism to pursue and neutralize rogue drones safely.
Projects
Selected work across academic research, startup product development, autonomous systems, and mechanical prototyping.
Developing an autonomous drone system that uses computer vision, target prediction, and a net-based capture mechanism to pursue and neutralize rogue drones safely.
Led mechanical development and system integration for automated restaurant technology, including prototype testing, mechanism design, PLC control, and deployment of automated vending systems.
Designed and integrated an autonomous delivery vehicle using ROS 2 on an NVIDIA Jetson platform with GPS, LiDAR, and visual tracking for automated last-mile delivery applications.
Payload tracking and control work involving gantry motion, camera-based perception, ROS 2 integration, and adaptive input shaping concepts for reducing swing.
Autonomous path tracking and controller development for a Quanser QCar platform using PID/LQR/NMPC concepts, localization, trajectory tracking, and performance evaluation.
Modeled and optimized fluid flow to reduce hydraulic resistance, improved testing throughput, and presented work on ambient temperature effects on thermosiphon efficiency.
Designed and simulated a CVT system in MATLAB, built a water brake dynamometer, and contributed to vehicle development for Formula SAE competition.