Design of a Multi-camera System with Compensation Algorithms for Real-time UAV Pose Estimation in Landing

Real-time UAV pose estimation at low altitudes is a necessary but challenging task for auto-landing, especially onto fluctuated aquatic surface platforms. To reduce the power and payload requirement for UAVs, pose estimation by the surface platform is an alternative. This paper presents a multi-camera system with compensation algorithms for that scenario. An accurate extrinsic calibration enables multi-camera collaboration to extend the system's field of view and improve its stability, which is inherently resistant to the issue of target-out-of-sight, motion blur effect, and over-exposure. Meanwhile, a compensation algorithm with Kalman Filter is applied to eliminate the negative effect of the image processing time and algorithm calculation delay, significantly improving the real-time performance of the system. A set of indoor and outdoor experiments validate the effectiveness of the proposed method, in which the measurement error is decreased by 50%.