Determining path, timing and velocity from a 3d accelerometer

In summary, the device can swivel over time which complicates the requirement to remove the gravity vector so as to figure out the true acceleration. Additionally, the accelerometer is not made for violent swings and as such it can clip the output based on excessive movement. There is a problem with clipping the information lost in this process.
  • #1
tdavis1198
2
0
Hi,

I wonder if there is anyone who can help me with a problem i have.

I have a device that includes a simple 3d accelerometer. The device is a handheld device and my challenge is to figure out the path that the device moves in space relative to its starting position. I would like to plot the path and velocity with time.

The challenge is that the device can swivel over time which means that the gravity vector changes and so it complicates the requirement to remove the gravity vector so as to figure out the true acceleration.

Additionally, the accelerometer is really not made for violent swings and as such it can clip the output based on excessive movement.

The type of movement that takes place is a repetitive movement and so the general path is known and as such i believe that a model of the gravity vector can be created. Someone has experimented with my data and used Kalman filters and cubic splines to try and figure out the information.

The path information and velocity does not have to be 100% accurate. I just need a good general trend of how the object moves and the timing.

I am not a physicist and my job would be to find an algorithm and then write the software in he embedded hardware. Time is of the essence and if there is someone who could help me figure this out, I would appreciate it.
 
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  • #2
Why subtract out the gravity vector? I would instead leave it in, and then at the very end, remove how far it has "fallen".

Clipping, though, is a problem. That information is lost, and the only thing you can do is try and guess what was lost.
 
  • #3
Vanadium 50 said:
Why subtract out the gravity vector? I would instead leave it in, and then at the very end, remove how far it has "fallen".
This is not a good idea; it is generally a very bad idea.

tdavis1198 said:
The challenge is that the device can swivel over time which means that the gravity vector changes and so it complicates the requirement to remove the gravity vector so as to figure out the true acceleration.
You obviously need some model of the attitude state, otherwise your integrated state will diverge rather quickly, even without gravity entering the picture. One approach is to use gyros as a means of estimating your attitude state.

Additionally, the accelerometer is really not made for violent swings and as such it can clip the output based on excessive movement.
This might be a big problem.
 
  • #4
D H said:
This is not a good idea; it is generally a very bad idea.

Why? Suppose you do this for one second, and then subtract off 16 feet. Why is this a problem?
 
  • #5
Vanadium, your approach might work if
  • Earth had a uniform (planar) gravity field.
    This is a valid approximation over a short distance, but if the travel occurs over any significant distance, the uniform gravity assumption fails. Even the spherical gravity assumption fails; NASA requires a waiver if manned spacecraft navigation algorithms use less than an 8x8 spherical harmonics gravity model.
  • The device holds steady attitude.
    This is definitely not the case here. The OP specifically said "the device can swivel over time".
  • You only cared about the state at the end (whenever that is).
    Typically one uses navigation techniques to get an estimate of the state (position, velocity) at every point in time, not just the end.

Accelerometers readings are chock full of errors: white noise, biases, scale factor errors, alignment errors, etc. Run-of-the-mill numerical integration techniques will result in a lousy answer, and that is assuming a proper accounting of the one force that accelerometers cannot measure (gravity). Overly simple numerical integration, without properly accounting for gravity, will result in an incredibly lousy answer. Kalman filters were developed to address this very problem. They are what correctly got the Apollo vehicles to the Moon.
 
  • #6
Would a Kalman filter help with the gravity problem or just to eliminate the noise?

PS. I need help to solve this problem and I am willing to pay somone to help!
 

Related to Determining path, timing and velocity from a 3d accelerometer

1. How does a 3d accelerometer determine path, timing, and velocity?

A 3d accelerometer measures changes in acceleration in three axes (x, y, and z), and uses this data to calculate the path, timing, and velocity of an object. By continuously measuring acceleration and integrating it over time, the accelerometer can determine the object's position, speed, and direction of movement.

2. What is the difference between path, timing, and velocity in the context of a 3d accelerometer?

Path refers to the movement of an object in space, while timing refers to the duration of that movement. Velocity is the rate of change of an object's position over time, and is a measure of both speed and direction.

3. How accurate is a 3d accelerometer in determining path, timing, and velocity?

The accuracy of a 3d accelerometer depends on several factors, such as the quality and calibration of the sensor, the sampling rate, and external factors like temperature and vibrations. Generally, modern accelerometers have a high level of accuracy, with errors within a few percentage points.

4. What are some common applications of using a 3d accelerometer to determine path, timing, and velocity?

3d accelerometers are commonly used in navigation systems, motion tracking devices, and fitness trackers. They are also used in various industries for monitoring and optimizing the performance of machines and equipment.

5. Can a 3d accelerometer determine path, timing, and velocity in all types of environments?

While 3d accelerometers can be used in a wide range of environments, extreme conditions such as high temperatures or intense vibrations can affect their accuracy. In these cases, special measures may need to be taken to ensure the reliability of the data collected by the accelerometer.

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