Vision-Aided IMU for Handheld Pedestrian Navigation
Vision-Aided IMU for Handheld Pedestrian Navigation
复制标题
用于手持式行人导航的视觉辅助 IMU
DOI：
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发表时间：
2010
期刊：
影响因子：
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通讯作者：
M. Andreotti
中科院分区：
文献类型：
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作者：
C. Hide;T. Botterill;M. Andreotti
低成本惯性传感器经常被宣传为室内导航的解决方案。然而，实际上，测量的质量很差，因此，传感器一次只能用于导航几秒钟，然后漂移就会变得太大而无法使用。因此，有必要定期使用来自外部系统（例如 GPS 或其他可用于导航的传感器）的测量值来更新传感器。计算机视觉社区提供了一种这样的传感器，其中可以使用相机来获取有关连续图像之间的相对平移和旋转的信息。本文介绍了如何使用连接到低成本 IMU 的摄像头在 GPS 不可用的区域（例如室内或城市峡谷深处）进行导航。假设行人用户正在行走，移动设备举在他们面前，相机大致指向地面。连续帧之间的特征进行匹配，并且使用强大的 RANSAC 框架来识别哪些帧位于地平面上，同时估计相机的方向和相对于其先前位置的 3 维身体框架平移。此信息用于帮助 IMU 使用卡尔曼滤波器来减少位置漂移。本文描述了计算机视觉和惯性导航相结合的方法的实现。战术级 IMU 用于初始测试，因为它提供更可靠的测量结果，并使我们能够提供参考来比较从计算机视觉算法获得的测量结果。事实证明，即使使用高质量的 IMU，该算法也能够在 GPS 测量不可用时显着提高 INS 导航的性能。
Low cost inertial sensors are often promoted as the solution to indoor navigation. However, in reality, the quality of the measurements is poor, and as a result, the sensors can only be used to navigate for a few seconds at a time before the drift becomes too large to be useful. Therefore, it is necessary to regularly update the sensors with measurements from external systems such as GPS or other sensors useful for navigation. One such sensor is provided by the computer vision community where a camera can be used to obtain information about the relative translation and rotation between successive images. This paper describes the use of a camera attached to a low cost IMU for navigation in areas where GPS is unavailable such as indoors or deep urban canyons. It is assumed that a pedestrian user is walking with the mobile device held out in front of them with the camera pointing approximately towards the ground. Features are matched between successive frames, and the robust RANSAC framework is used to identify which of these lie on the ground plane, while estimating the camera’s orientation and 3 dimensional body frame translation relative to its previous position. This information is used to aid the IMU using a Kalman filter to reduce the position drift. This paper describes the implementation of the combined computer vision and inertial navigation approach. A tactical grade IMU is used for initial testing since it provides more reliable measurements and enables us to provide a reference by which to compare the measurements obtained from the computer vision algorithm. It is demonstrated that even with a good quality IMU, the algorithm is able to significantly improve the performance of INS navigation when GPS measurements are unavailable.