Infrared lights-based monocular pose measurement for autonomous rendezvous of dual-motion platforms

Real-time and accurate relative pose measurement is one of the key technologies for autonomous interaction of dual-motion platforms. The monocular pose measurement method has drawn wide attention from researchers because of its advantages of simple configuration, low cost, etc. In this paper, an Infrared lights-based monocular pose measurement for autonomous interaction of dual-motion is proposed. First, a specific number of infrared LEDs are deployed on the target platform. The targets are detected via Pixels-priori adaptive threshold segmentation on the infrared image, then sub-pixel coordinates are acquired through a moment-based method. Second, a Random Perspective-3-Points (P3P) method is exploited to identify the 2D-3D correspondences. Finally, on the assumption of constant velocity model, the Gaussian- Newton optimization method is adopted to achieve precise and efficient pose tracking. The UAV autonomous landing experiments demonstrate that the proposed method realize real-time and accurate pose estimation, which successfully guide the UAV landing on the roof of the vehicle.