A Robust Pose Estimation Method for Multicopters Using Off-Board Multiple Cameras

Pose estimation is an important issue for the visual servoing of multicopters. With a process model customized for multicopters and a generic camera model, an extended Kalman filter (EKF) method is proposed in this paper to estimate the pose of multicopters based on off-board multiple cameras. In consideration of EKF implementation, a general point correspondence method that can deal with any number of feature points and cameras is further designed. The proposed EKF method is applicable to not only a single fish-eye (or conventional) camera but also multiple fish-eye (or conventional) cameras. Observability analysis and experiment results show the proposed EKF method is more robust against noise and marker missing than existing filtering methods.