姿势
计算机视觉
人工智能
计算机科学
全球定位系统
卡尔曼滤波器
解码方法
单眼
扩展卡尔曼滤波器
三维姿态估计
关节式人体姿态估计
单目视觉
算法
电信
作者
Xudong Yan,Heng Deng,Quan Quan
标识
DOI:10.1109/iros40897.2019.8967660
摘要
Relative pose estimation is critical for collaborative multi-agent systems. To achieve accurate and low-cost localization in cluttered and GPS-denied environments, we propose a novel relative pose estimation system based on a designed active infrared coded target. Specifically, each agent is equipped with a forward-looking 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 GPS-denied environments.
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