A Monocular Target Pose Estimation System based on An Infrared Camera We present an accurate and robust pose estimation system based on infrared reflective markers and a monocular camera with an infrared filter. The infrared reflective markers are pasted on target object and the camera is mounted on the mobile robot. In the system initialization phase, the correspondence between the markers and image observations are calculated by our correspondence search algorithm. After the initialization, correspondence between markers and observations can be predicted with pose computed in last frame. Thereafter, P2P algorithm based on LevenbergMarquardt is applied to optimize the pose of the current frame. The experiment result shows that our system has larger positioning range than ArUco markers. In addition, this method can estimate object pose in most perspective and is robust to occlusion.

Active Infrared Coded Target Design and Pose Estimation for Multiple Objects Relative pose estimation is critical for collaborative multiagent systems. To achieve accurate and lowcost localization in cluttered and GPSdenied environments, we propose a novel relative pose estimation system based on a designed active infrared coded target. Specifically, each agent is equipped with a forwardlooking monocular camera and a unique infrared coded target. The target with the unique lighted LED arrangement is detected by the camera and processed with an efficient decoding algorithm. The relative pose between the agent and the camera is estimated by combining a PnP algorithm and a Kalman filter. Various experiments are performed to show that the proposed pose estimation system is accurate, robust and efficient in cluttered and GPSdenied environments.