10
votes
Accepted
How can we use the accelerometer for altitude estimation?
The barometer carried on the pixhawk has an altitude resolution of 10 cm. If that isn't enough, you could write a kalman filter that uses the accelerometer data in the prediction step and the ...
- 1,853
7
votes
Open source implementations for GPS+IMU sensor fusion?
Yes. The px4 software for the pixhawk autopilot has an extended kalman filter that uses an accelerometer, a gyroscope, gps, and mag.
A paper describing the a smaller ekf which only estimates attitude ...
- 1,853
4
votes
Open source implementations for GPS+IMU sensor fusion?
ROS has a package called robot_localization that can be used to fuse IMU and GPS data. This package implements Extended and Unscented Kalman filter algorithms.
The package can be found here.
- 378
4
votes
Accepted
Balancing a plate with an IMU offset from the center
Basically it does not matter.
But you have to be carefull if the plate is rotating fast, because the rotation of the plate around its center point, with the IMU placed out of center, will cause the ...
- 1,657
3
votes
Overcorrecting Kalman Filter
There is an error in your posted equation for the Jacobian $F_J$, so that could be the source of the problem. It should look like this:
$F_J = \begin{bmatrix}
1 & 0 & -C \sin \theta \\
C \...
- 1,377
3
votes
Need help regarding development of Extended Kalman Filter for sensor-data fusion of odometry and IMU data
Adding to the above, my favorite way to debug a misbehaving filter is to isolate each step.
Make sure your prediction step works before correcting it. Your bot should drive straight right with 0,0,0 ...
- 5,312
3
votes
Accepted
Transforming angular velocity?
I think your diagram is missing an angle for the laser angle with respect to the vehicle body -- I'm going to call that angle $\alpha$, see this diagram for clarity:
Since it seems you are tracking ...
- 1,377
3
votes
Accepted
quaternion implementation
So, as I mentioned in an earlier comment, it looks like you're using a mashup of methods. You're not applying any one method correctly; instead you're mis-using part of one method, then using the ...
- 16k
3
votes
Will there be any interference when distance sensors facing each other?
The amount of interference highly depends on the sensor type and how you use them.
One of the worst for this is probably ultrasonic rangers:
These are going out of fashion now, but older robots used ...
Ben♦
- 5,825
3
votes
How to deal with asynchronous samples in a kalman filter framework multi-sensor fusion?
The correct way of integrating multi-rate observations in a Kalman framework when the measurements are unavailable is to let the system evolve resorting merely to the prediction steps.
Therefore, set ...
- 3,995
2
votes
Open source implementations for GPS+IMU sensor fusion?
A followup on holmeski's reply.
It seems those pages have been taken down.
I found the old webpages on the 'Way Back Machine'.
Pixhawk Attitude Estimator (EKF)
Pixhawk ekf_att_pos_estimator (...
- 21
2
votes
Need help regarding development of Extended Kalman Filter for sensor-data fusion of odometry and IMU data
You should first validate your filter is working before second-guessing your modelling choices. But I agree both those filters look OK (although I did not double check all the maths) and both of your ...
- 892
2
votes
Accepted
Robot positioning using IMU quaternion data?
The quaternion only contains information about the rotation of the vehicle. It will not contain information about the location of you vehicle on a 2-d plane.
One method of converting quaternions to ...
- 1,853
2
votes
Gyro Yaw Drift Compensation With The Aid of Magnetomer
my roll and pitch drifts are corrected with accelerometer inside IMU
You mean they're being correct by the IMU, or you're correcting the readings yourself using the accelerometer from the IMU?
i ...
- 16k
2
votes
Is it possible to track position using gyroscope and accelerometer without a magnetometer?
The short answer is that it's possible, but tricky.
To estimate position you integrate accelerometer readings over time to get linear velocity estimates, and then integrate the velocities to get ...
- 1,353
2
votes
Accepted
EKF sensor fusion
An EKF or any of the variants of the Kalman filter, as you said mainly works in two steps: prediction and correction. The prediction steps gives you a state estimate based on your process model and ...
- 124
2
votes
Bias correction for multiple sensor fusion through Kalman Filtering
Your state vector $x$ is correct.
When you do bias estimation(look up IMU kalman filters) you assume that the bias is constant/slowly varying. So your $F$ matrix is just the identity(5x5).
Your $H$ ...
- 1,831
2
votes
Accepted
GPS Course vs IMU Course
So this probably won't work as course over ground and heading are often 2 different things. Heading is the direction your vehicle is facing, while course over ground is the direction your vehicle is ...
- 1,831
2
votes
No difference between UKF and EKF for SLAM
The EKF is a first-order approximation, which is achieved by linearizing the system about the current state estimate (i.e., the mean). In some cases, the EKF is not stable due to nonlinearities. For ...
- 335
2
votes
How to actually fuse sensor using Extended Kalman Filter
I've never worked on Mecanum wheels before so I researched a bit. One of the first things I look for is there has to be a way to combine all of the encoder velocity measurements. Apparently, Jacobian ...
- 21
2
votes
Accepted
How to use knowledge of sensor noise
You are correct. It's just a matter of interpretation.
(1) is the guess on the location of the true value whereas (2) is simulating your sensor behavior.
Your equation in (1) can be converted to N(z,...
- 1,527
2
votes
Accepted
What would be a way to estimate IMU noise covariance matrix?
Usually, IMU manufacturers implement some kind of filter to remove the noise these days, therefore the probability is your IMU is not throwing raw values. Nevertheless, you can initiate the sensor ...
- 536
2
votes
Merging multiple LIDARs real time
Certainly merging two laser scans into a single point cloud is doable. Here's an example tool and you can easily concatenate said point clouds too.
However I'd like to suggest that you reconsider some ...
- 24.7k
2
votes
accelerometer and gyroscope fusion using extended kalman filter
You should be using quaternions for fusion for good behaviour. Addition and multiplication for quaternions will be swapped out by rotation composition operations for quaternions and your orientation ...
- 128
1
vote
How does sensor fusion related to SLAM?
Sensor fusion is a process where you are gathering information from one or more sensors and inputting that data to your processor to process the data to make sense whether it is useful or not.
In ...
- 183
1
vote
calibrating large scale manipulator
You are not the first person in the world that wants to calibrate a larger robot, so there are commercially available solutions :)
The tool of choice in your case is a laser tracker. You attach one ...
- 1,355
1
vote
How to handle multi-sensors data?
I think doing things probabilistically is a good approach. You have to realize that your sensors aren't perfect. You have to contend with things like noise, false positives, false negatives, limited ...
Ben♦
- 5,825
1
vote
Yaw drift when implementing AHRS filter fusion
You haven't provided any sample data or your implementation, etc., so it's hard to say for sure, but I would imagine that the signal coming in on your magnetometer is small enough that it's ...
- 16k
1
vote
Position Estimates from sensor fusion
Usually SLAM needs some kind of a localization to build the map. I'm not clear what kind of a method you are using for SLAM. But for your question, you can estimate the position from your IMU ...
- 354
1
vote
How to do IMU and camera "sensor fusion" tracking?
The easiest platform for a multi-modal sensor fusion is a continuous-time trajectory model. Please have a look at this repo and related papers. I believe that it should be state of the art ...
- 1,527
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