MPC-based Visual Servo Control for UAVs

Examiner: Dimos Dimarogonas

Abstract: Vision information is essential for planning and control of autonomous systems. Vision based control systems leverage rich visual input for motion planning and manipulation tasks. This thesis studies the problem of Image-Based Visual Servo (IBVS) control for quadrotor UAVs. Despite the effectiveness of vision-based systems, the control of quadrotors with IBVS presents the non-trivial challenge of matching the 6 DoF control output obtained by the IBVS with the 4DoF of the quadrotor. The novelty of this work lies in addressing the under-actuation problem of quadrotors using linear Model Predictive Control (MPC). We extensively evaluate the performance of the designed solution on both simulated environment and real-world experiments.