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Camera and inertial sensor fusion for the PnP problem: algorithms and experimental results
Machine Vision and Applications ( IF 2.4 ) Pub Date : 2021-06-05 , DOI: 10.1007/s00138-021-01219-0
Luigi D’Alfonso , Emanuele Garone , Pietro Muraca , Paolo Pugliese

In this work, we face the problem of estimating the relative position and orientation of a camera and an object, when they are both equipped with inertial measurement units (IMUs), and the object exhibits a set of n landmark points with known coordinates (the so-called Pose estimation or PnP Problem). We present two algorithms that, fusing the information provided by the camera and the IMUs, solve the PnP problem with good accuracy. These algorithms only use the measurements given by IMUs’ inclinometers, as the magnetometers usually give inaccurate estimates of the Earth magnetic vector. The effectiveness of the proposed methods is assessed by numerical simulations and experimental tests. The results of the tests are compared with the most recent methods proposed in the literature.



中文翻译:

PnP 问题的相机和惯性传感器融合:算法和实验结果

在这项工作中,我们面临估计相机和物体的相对位置和方向的问题,当它们都配备惯性测量单元(IMU),并且物体展示一组具有已知坐标的n 个地标点(所谓的姿势估计或 P n P 问题)。我们提出了两种算法,融合相机和 IMU 提供的信息,解决 P nP 问题,精度很好。这些算法仅使用 IMU 倾角计给出的测量值,因为磁力计通常会给出不准确的地球磁矢量估计值。通过数值模拟和实验测试来评估所提出方法的有效性。将测试结果与文献中提出的最新方法进行比较。

更新日期:2021-06-05
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