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Precise Positioning of Robots with Fusion of GNSS, INS, Odometry, Barometer, Local Positioning System and Visual Localization

机译:机器人的精确定位具有GNSS,INS,IDOMOTRY,晴雨表,局部定位系统和视觉定位的融合

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The autonomous driving of robots requires precise and reliable positioning information with low-cost sensors. In this paper, we propose a tightly coupled sensor fusion of multiple complementary sensors including GNSS-RTK, INS, odometry, Local Positioning System (LPS) and Visual Positioning. The focus of this paper is on the integration of LPS and vision since the coupling of GNSS-RTK, INS and odometry is already state of the art. We include the positions of the LPS anchors and the bearing vectors and distances from the robot's camera towards the patch features as state vectors in our Kalman filter, and show the achievable positioning accuracies.
机译:机器人的自主驱动需要具有低成本传感器的精确且可靠的定位信息。在本文中,我们提出了一种紧密耦合的多个互补传感器的传感器融合,包括GNSS-RTK,INS,IDOMOTRY,局部定位系统(LPS)和视觉定位。本文的焦点是由于GNSS-RTK,INS和OCOMOTRY的耦合是本领域的耦合,因此LPS和视觉的集成。我们包括LPS锚和轴承向量的位置和轴承矢量和轴承矢量的距离,朝向贴片功能作为我们的卡尔曼滤波器中的状态向量,并显示了可实现的定位精度。

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