Pose estimation of a volant platform with a monocular visuo-inertial system

One of the serious problems in robotics applications is the estimation of the robot's pose. A lot of research effort has been put on finding the pose via inertial and proximity sensors. However, the last decades many systems adopt vision to estimate the pose, by using homographies and projection geometry. In this paper the pose estimation is achieved by the identification of a geometrically known platform from one camera and from the measurements of an inertial unit. The extended Kalman filter (EKF) is used for data fusion and error compensation. The novelty of this system is that the visual sensor and the inertial unit are mounted on different mobile systems. The proposed pose estimation system exhibits high accuracy in real-time.