iOS 设备上的传感器融合

本文介绍了iOS 设备上的传感器融合的处理方法，对大家解决问题具有一定的参考价值，需要的朋友们下面随着小编来一起学习吧！ 问题描述

我想知道如何开始在 iPhone 上实现传感器融合.我从 David Sachs 的这个演讲开始:

I'm trying to find out how could I start to implement sensor fusion on the iPhone. I've started from this talk from David Sachs:

Android 设备上的传感器融合

尽管 David 的演讲非常具有说明性，但并没有显示任何代码(这是有道理的).我已经看到了 GLGravity(提取重力矢量)和AccelerometerGraph 示例，但我需要一些帮助或至少指导结合加速度计、陀螺仪和罗盘输入，使结果与 David 显示的相似.

Although David's talk is very illustrative, it doesn't show any code (it makes sense). I've seen both the GLGravity (to extract the gravity vector) and the AccelerometerGraph examples, but I need some help or at least guidance on how to combine the accelerometer, gyroscope and compass inputs so that the result is similar to what David shows.

谢谢

推荐答案

更新: 截至 2015 年 5 月 19 日，在移动设备上自行实施传感器融合毫无意义:Android (SensorManager)和 iPhone (CMAttitude 下的 noreferrer">Core Motion 提供了它自己的.

UPDATE: As of May 19, 2015, there is no point in implementing sensor fusion yourself on mobile devices: Both Android (SensorManager under Sensor.TYPE_ROTATION_VECTOR) and iPhone (Core Motion under CMAttitude) offers its own.

(2011 年 5 月 5 日的原始答案)

我已经为 Shimmer 2 设备实现了传感器融合，基于这个手稿.我强烈推荐它.

I have implemented sensor fusion for Shimmer 2 devices based on this manuscript. I highly recommend it.

传感器融合通常通过卡尔曼滤波器实现.

Sensor fusion is often achieved by Kalman Filter.

然而，没有程序员的卡尔曼滤波器"这样的东西.卡尔曼滤波器很难理解.如果您不了解它，您将无法正确实施和使用它.就用上面的手稿.

However, there is no such thing as "Kalman Filter for programmers". Kalman filter is difficult to understand. You won't be able to implement and use it correctly if you do not understand it. Just use the above manuscript.