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

我试图找出如何开始在iPhone上实现传感器融合。我从David Sachs的演讲开始：

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

虽然David的讲话非常具有说明性，但它没有显示任何代码（这很有意义）。我已经看过 GLGravity （提取重力矢量）和 AccelerometerGraph 示例，但我需要一些帮助或至少指导如何将加速度计，陀螺仪和罗盘输入结合起来，结果与David所示的相似。

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现传感器融合没有任何意义：Android（ SensorManager Sensor.TYPE_ROTATION_VECTOR ）和iPhone（ CMAttitude 下的pple_ref / occ / cl / CMAttituderel =nofollow noreferrer> Core Motion 提供了自己的。

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）

我为 Shimmer 2实施了传感器融合基于此稿件的设备。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。

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。如果您不理解它，您将无法正确实现和使用它。只需使用上面的手稿。

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.