Vision Sensor-Based Human Tracking Control of a Quadcopter UAV with Position Uncertainty

Abstract

In this paper, we describe a method for the attitude of a quadcopter UAV using image information of a moving object like a walking human. This method combines the observed position from GPS sensors and the estimated position from the images captured by a UAV’s camera to localize a walking human. Using the a priori known path of a quadcopter UAV in world coordinates and a perspective camera model, we derive the geometric constraint equations which represent the relation between image frame coordinates for a moving object and the estimated quadcopter UAV's attitude. The proposed method utilizes the error between the observed and estimated image coordinates to localize the quadcopter UAV. The Kalman filter scheme is applied for this method. The performance of proposed algorithm is verified by the computer simulation and the experiments.