室内跟踪（IMU +标签） [英] Indoor tracking (IMU + tags)

问题描述

这是关于室内跟踪使用惯性的其他问题（智能手机+ aceel +陀螺仪） 首先，我想说，我已经阅读计算器谈这个话题，几乎每一个岗位。 而且我知道，为跟踪的位置，我们将不得不整合两倍的加速，然后这是非常无用的，因为所有的漂移误差的实际生活中的应用......

this is an other question about indoor tracking using inertial (smartphone + aceel + gyro) Firstly I would like to say that I have read almost every post on stackoverflow talking about this subject. And I know that to track a position We will have to integrate TWICE the accel and that is very useless in a real life application because of all the drift errors...

不过，事实证明，我并不需要建立一个平面或什么，我也没必要developp有工作要出售或东西的应用程序。我只是想知道，用一个简单的Andr​​oid应用程序的室内跟踪理论的概念 -

But it turned out that I don't need to build a plane or whatever And i don't need to developp an application that have to WORK to be sold or something . I just want to realize a simple Android App that use "theoretical" concept of an Indoor tracking-

• 有什么可能性？
• 我们需要什么？

基本上我的手机是休息一台屏幕面朝上在已知位置（0,0），如果把我的手机2或3计和然后我转动它，我又推2〜3 计我后多少米就变得不准确看到一个这样使用一个标签屠重新校准测量＆LT; ---这是我的主要问题

Basically my phone is resting on a desk screen facing UP at a known position (0,0) if a push my phone to 2 or 3 meter and then i rotate it and i push it again for 2 or 3 meter I the to see after how many meter it becomes to inaccurate an so use a tag tu recalibrate the measurements <--- That's my main question

我需要什么？ - 角度α （OK整合陀螺仪）（我不想使用指南针） - 在加速？ （我有） - 速度？ （整合加速） - 和位置（双加速整合）

what do I need ? - the angle ? (ok integrating the the gyro) (i don't wanna use the compass) - the accel? (i have) - the velocity ? (integrating the accel) - and the position (double accel integration)

这是我想知道的是我怎样才能把这个号码一起？是不是正确的方式做到这一点？是否有其他解决办法（来解决我的问题不跟踪有人真的准确）？

The thing that I would like to know is How can i put this number together? Is it the right way to do it? Is there an other solution (to resolve my problem not to track someone really accurately)?

我也看了看DCM的theorie（如果我undertood正确的，它会给我电话的方向在6轴吧？但是，我们获得的加速度或陀螺仪（俯仰角度的差异，滚等..）？

I also looked at the theorie of the DCM ( If I undertood correctly it will give me the orientation of the phone in 6 axes right? But what the difference about getting the angle from the accel or the gyro (pitch, roll etc..) ?

感谢您

推荐答案

随着你，不考虑计算能力，在这一点上还没有传感器，我知道位置/位移估计只有一个方法。这要么仅涉及光流与车载用相机，或上述与addidional信息从融合的数据从ACCELS /陀螺仪（例如，与一个卡尔曼滤波器）来提高精度。我想 OpenCV的拥有所有你需要（包括对Android的支持），所以我会从那里开始。

With the sensors you have, not considering computational power at this point yet, I know of only one method of position / displacement estimation. This would either involve just optical flow with the onboard camera, or the above with addidional info from fused data from accels / gyros (eg. with a Kalman-Filter) to improve accuracy. I guess OpenCV has all you need (including support for Android), so I'd start there.

首先实施的态度，估计只有学院的优势和陀螺仪。这将在偏航轴线（垂直于地面即轴线，或者说平行于重力矢量）漂移。这可以用一个卡尔曼滤波器或其它算法来完成。这会不会是什么好了位置估计，因为估计的位置将在短短的几秒钟漂移米的十分之一了。

Start by implementing an attitude-estimator with just accels and gyros. This will drift in yaw-axis (ie. the axis perpendicular to the ground, or rather parallel to gravity vector). This can be done with a Kalman-Filter or other algorithms. This won't be any good for position estimation, as the estimated position will drift tenths of meters away in just a couple of seconds.

然后尝试实现你的摄像头，这在计算上是昂贵的光流。其实这本身可能是一个解决方案，但精度比从IMU额外的数据较少。

Then try implementing optical flow with your camera, which is computationally expensive. Actually this alone could be a solution, but with less accuracy than with additional data from an IMU.

祝你好运。

修改：我最近发现这 - 它可能对你有所帮助。如果没有大量的噪音（由于振动），这将工作（我在一个quadrotor无人机，它遗憾的是不工作对我来说）。

EDIT: I recently found this - it may be helpful to you. If there is not a lot of noise (due to vibration), this would work (I'm on a quadrotor UAV and it unfortunately doesn't work for me).

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