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2013-03-22 01:41:02 -0500 | asked a question | how to calculate covariance Hey! I am looking for the error covariance of two sensors (gyro & accelerometer). Since I do have the data sheets I was wondering if you could tell me how to obtain the value. I do know that the covariance might change but is there a way to estimate it from noise specifications or something similar? In both cases I have the power spectral density of the noise. Is this the value I need? The information I am referring to is on page 12 and page 13 in this http://www.invensense.com/mems/gyro/documents/PS-MPU-6000A.pdf (document). Thanks for any suggestions :) |
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2013-03-20 20:40:31 -0500 | commented answer | Quaternion to Roll, Pitch, Yaw you must also copy the value of w from the target state. The Quaternion consists of 4 values. I probably would put all the conversion and publishing inside the if (fresh_data == true) loop. Or you could publish in the callback function and use q_rot directly |
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2013-03-20 12:12:50 -0500 | answered a question | Quaternion to Roll, Pitch, Yaw Could you be more specific on what does not work? Since you say Now all you have to do is write this information in a message of your choice and publish it. For some reason the For the Publishing: If you want to publish inside the and globally: and below your node handle: hope I did not forget something :) edit: Oh you got it but there are incorrect values. Sorry, but I think I can not help you there. Maybe you could check if the error is in some way related to pi/2 or the values are exchanged. Then you could adapt your coordinate system... edit2: Did you just initialize q in the |
2013-03-18 12:59:59 -0500 | answered a question | plot/print rpy from quaternion Hey, here is a c++ solution to your problem :) just in case you still have use for it! Needed the transformation from quaternion to rpy-angles too so here is what I put together. Used the code fragment from http://answers.ros.org/question/36977/invalid-arguments-convert-from-quaternion-to-euler/ (here) for the actual transformation. |