Sensor fusion using extended kalman filter

AI Thread Summary
The discussion focuses on implementing sensor fusion using an Extended Kalman Filter (EKF) for two three-axis accelerometers and encoder data in a mobile robot navigation system. The user seeks guidance on modeling the plant and measurement for state estimation, specifically defining the states as position coordinates (x, y) and heading angle (theta). There is a request for assistance in fusing data from accelerometers and encoders to improve robot pose estimation, along with a query about the necessity of a gyroscope. Participants emphasize the importance of providing detailed information about previous work and using proper language for effective communication. Overall, the thread highlights the challenges faced by beginners in applying EKF for sensor fusion in robotics.
SUDHEER87
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hi all,
m trying to implement sensor fusion of two three axis accelerometers data.can anyone help me in modelling this sensor and fusing for state estimation using EKF?
thanks in advance.!
 
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What are the states? Measurements? And what have you done so far?
 
chingkui said:
What are the states? Measurements? And what have you done so far?

thanx 4 your kind reply..,iam just a beginner.Right now iam surveying the literature regarding kalman filter.im using ADXL345 accelerometers..,kindly help me in choosing plant model and measurement model...!

thanq
 
chingkui said:
What are the states? Measurements? And what have you done so far?

can u pls help??
 
We can help, BUT

You need to drop the text speech. Try to use proper English. We don't expect perfect English, but we do want you to try.

You need to give us a little bit to work with. Show some work, answer problems when asked (e.g., post #2).

Do not ask us to do all of your work for you.

Do not ask us to write a book.
 
chingkui said:
What are the states? Measurements? And what have you done so far?

hi..!

Iam trying to implement a mobile robot navigation system based on extended kalman filter. I need to fuse the data from the encoders with the two accelerometer's data. The states are: Xk={x,y,theta} where x,y are the coordinates and theta is the heading angle.
Can anyone help me in fusing the data from encoders and accelerometers to get good estimate of the robot pose? And is gyroscope necessary in this??

Thanks in advance..!
 

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