Naga Venkata Dheeraj Chilukuri
Robotics and autonomous systems
Hometown: Gudivada, Andhra Pradesh, India
Graduation date: Fall 2025
MORE | Fall 2025
Experimental Evaluation of Model-free Framework for Fault Detection and Identification
Fault detection is essential for maintaining the safety of unmanned aerial vehicles (UAVs). Traditional approaches rely on model-based residuals that often fail under system uncertainties. This research evaluates a model-free neural framework for real-time fault detection and identification (FDI) in quadrotor systems. The framework eliminates dependence on mathematical models by learning fault patterns directly from data. Simulation and hardware experiments using Crazyflie drones with induced motor faults will evaluate detection accuracy, latency, and recovery performance, advancing safer and more resilient autonomous flight control.
Mentor: Kunal Garg
It’s hip to be square.
Students presenting projects at the Fulton Forge Student Research Expo are encouraged to download this personal QR code and include it within your poster. This allows expo attendees to explore more about your project and about you in the future.
Right click the image to save it to your computer.