Speaker: Mr. Fethi Ouerdane, Graduate Student, Control and Instrumentation Engineering Department

Abstract:

This study presents a novel approach for testing visual serving on 3 DOF UAVs (Unmanned aerial vehicles) in an indoor environment with no GPS by employing a combination of a physical 3 DOF and simulating the rest of the degree; 2D markers are used to store instructions to previously known coordinates in the environment. Low-cost UAV hardware with an onboard camera can extract the task information from such markers without needing a ground station computer and continuous marker detection to follow a particular desired trajectory. Such a goal is achieved through the presence of markers, such as QR (Quick Response) codes, at selected locations, controlling the UAV motion to read and extract the stored information in the code, and controlling various states of UAV to fulfill the desired motion of moving through the site. This solution combines simulation and physical testing such that the final algorithm can be applied on 6 DOF UAVs for asset monitoring and inspection in indoor environments, and non-experts can modify the vehicle’s path by providing the QR codes. Experimental results for the centering of UAV for accurate QR code reading using PID (Proportional-Integral-Derivative) controller and LQR (Linear Quadratic Regulator) algorithm for attitude control are tested on Quanser’s 3-DOF hover quadcopter in LabVIEW environment. Furthermore, hardware-in-the-loop simulation tests are performed to simulate the control of the linear motion of the UAV. The results achieved so far are promising and give ample encouragement to test and evaluate the technique on a 6-DOF UAV.

Speaker Bio:

Mr. Fethi Ouerdane is a Master’s student in the Department of Control and Instrumentation Engineering at King Fahd University of Petroleum and Minerals (KFUPM). His research focuses on image-based control systems and computer vision, with particular interest in their applications in autonomous navigation and robotics. Mr. Fethi holds a Bachelor’s degree in Electrical Engineering and has collaborated on projects involving real-time object detection and tracking.

All Faculty, Researchers, and Graduate Students are invited to attend.