利用低成本惯性传感器和基于标记的视频跟踪进行室内三维位置估计

Bastian Hartmann, N. Link, G. Trommer
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引用次数: 30

摘要

本文提出了一种基于惯性测量单元的室内三维位置跟踪系统和利用外部摄像机的基于标记的视频跟踪系统。与综合导航系统类似,3D位置、速度和姿态由IMU测量计算,并辅以视频跟踪系统的位置修正。来自两个传感器源的测量结果与扩展卡尔曼滤波模型融合,该模型包含视频中断期间漂移补偿的IMU偏差估计。滤波方法的性能已经用模拟数据进行了测试,整个系统已经用来自手部跟踪场景的真实数据进行了评估。通过结合惯性传感器和基于视觉的位置跟踪,该系统能够克服短时间内视频测量中断以及IMU的漂移问题。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Indoor 3D position estimation using low-cost inertial sensors and marker-based video-tracking
In this paper, a system for indoor 3D position tracking with an inertial measurement unit and a marker-based video tracking system utilizing external cameras is presented. Similar to an integrated navigation system, 3D position, velocity and attitude are calculated from IMU measurements and aided by using position corrections from the video tracking system. The measurements from both sensor sources are fused with an extended Kalman filter model, which incorporates the estimation of IMU biases for drift compensation during video outages. The performance of the filter approach has been tested with simulated data and the whole system has been evaluated with real data from a hand tracking scenario. By means of the combination of inertial sensors and vision-based position tracking, the proposed system is able to overcome video measurement outages over short periods of time as well as drift problems of the IMU.
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