使用加速度计计算距离 [英] calculating distances using accelerometer

问题描述

在阅读了许多关于如何根据加速度数据测量距离的研究和论文后，除了许多论坛我找到了二重积分法，但是这个方法相关的误差很大，而且随着时间的推移而增加.此外，我发现一些人建议使用卡尔曼滤波器，我阅读了一些关于它的参考资料，但我不清楚如何使用它.还有一些人在谈论融合传感器……但在阅读它们之后我没有得到任何新的想法.所以我仍然很困惑，我没有找到正确的答案......抱歉这么长的介绍.

After reading many researches and papers beside to many forums about how to measure the distance based on the acceleration data I found the double integration method, but the error related to this method is big and increases by time. In addition I found some people who suggested Kalman filter I read some references about it but it was not clear to me how to use it. also some were talking about the fusion sensors ... but after reading them I did not get any new ideas. so I am still confused and I did not find the right answer to follow .... sorry for this long introduction.

问题

让我们考虑一下，我手里拿着 9 轴传感器，我的手向某个方向移动，我如何才能找到我的手在空间中的新位置?如何获得从初始点到新点的运动矢量我的意思是如何知道三个轴上的通过距离?

Let us consider that I hold 9-axis sensor in my hand and I move my hand in some direction, how I can find the new position of my hand in the space? how to obtain motion vector from the initial point to the new point I mean how to know the passed distances on three axes?

如果没有直接的答案......一些建议或参考会很好，或者一些给出准确答案的算法，我可以自己研究和使用它.非常感谢

If there is no direct answer ... some advises or references would be great or some algorithms that give an accurate answers and I can study and use it by myself. thank you very much

推荐答案

对您问题的简短回答是您做不到.

The short answer to your question is you can't do it.

双积分方法确实是仅使用加速度计获取您正在寻找的信息的唯一方法.你发现了这个方法的问题.误差会随着时间的推移而增加，并且通常无法达到许多人所期望的准确度.

The double integration method is really the only way to get the information you are looking for using only an accelerometer. You found the problem with this method. The error increases over time and generally doesn't give the accuracy many are looking for.

卡尔曼滤波通常需要 2 个设备，并且基本上可以充分利用这两个设备的优点并滤除坏的.请参阅下面的示例.

Kalman filtering usually requires 2 devices and basically takes the best of both devices and filters out the bad. See example below.

卡尔曼滤波是一个非常艰难的主题，我试图深入研究高级设计，但在我有限的测试中从未发现任何有意义的结果.这个youtube视频是开始理解这个主题的好地方系列.

Kalman filtering is a really tough subject that I tried to dive into for senior design, but never found any meaningful results with my limited testing. A great place to start understanding this subject is with this youtube video series .

这个人在斯坦福大学赢得了 DARPA 挑战，并以易于理解的方式解释了这个话题.整个课程是一个 6 个单元的视频系列，内容涉及编程机器人以在未知环境中移动和了解其位置.如果您有时间和兴趣，值得一看.

This is the guy that won the DARPA challenge with Stanford and explains the topic in an easy to understand way. The whole course is a 6 unit video series about programming robots to move and understand their location in an unknown environment. Worth a watch if you have the time and interest.

听起来您正在尝试做一些类似于我为高级设计所做的工作，以提供非常具体的相对位置信息.

It sounds like you're trying to do something similar to what I did for senior design in give really specific relative location information.

另一个伟大的卡尔曼滤波 阅读此内容(如果此链接无法使用 TKJ 平衡过滤器，则单击 TKJ 链接 google bot 链接无效).基本上这个家伙使用加速度计和陀螺仪来跟踪现实世界中的方向.

Another great Kalman filtering read this (if this link doesn't work google Kalman filter balance bot and click the TKJ blog link). Basically this guy uses an accelerometer and gyroscope to track orientation in the real world.

其他可以查看 wiki 实时运动学的内容.这适用于拖拉机并结合起来提供真正准确的位置信息.John Deere 出售一个系统，但它的价格为 20,000 美元.这是使用 GPS 和 beagleboard

Something else to look into wiki Real Time Kinematic. This goes on tractors and combines to provide really accurate location information. John Deere sells a system, but it's like $20,000. Here is the poor man's version using GPS and beagleboard

这篇关于使用加速度计计算距离的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持IT屋！