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I wonder, why the IMU is not calibrated by factory configuration. Could you at least provide some "factory spec" one, which I could upload to eeprom? In eeprom we now only have
And also provide some bias/noise estimates (perhaps from manufacturer?), which should also have a place in the json-format.
At least, there should be a tool, to do calibration for your own (perhaps you could add it to your "calibrate.py" script). It is needed for every task, where IMU and camera are combined, for example VIO/SLAM. I think robotics is a common use case for oak-d, where then additional AI features are applied.
Btw: I got one of the early oak-d kickstarter devices with calibration for only two of the three cameras. So some spec-intrinsic/extrinsics for all devices would also be nice. Perhaps there could be a collection here on github?
The text was updated successfully, but these errors were encountered:
Hi @cyberbeat ,
I haven't personally tried this, but Arducam engineers wrote a tutorial on how to calibrate the IMU. Could you try that out? And please provide a feedback if it works as expected.
Thanks! Erik
Hi @cyberbeat , I haven't personally tried this, but Arducam engineers wrote a tutorial on how to calibrate the IMU. Could you try that out? And please provide a feedback if it works as expected. Thanks! Erik
Hi,
this doesn't work on ros2. I guess kalibr is designed for ros1. Do you have any other suggestion?
Hi, you can use ROS1 version of the driver to calibrate the IMU, with V3 release of depthai-core there will be also some initial calibration values based on data in depthai-boards
I wonder, why the IMU is not calibrated by factory configuration. Could you at least provide some "factory spec" one, which I could upload to eeprom? In eeprom we now only have
And also provide some bias/noise estimates (perhaps from manufacturer?), which should also have a place in the json-format.
At least, there should be a tool, to do calibration for your own (perhaps you could add it to your "calibrate.py" script). It is needed for every task, where IMU and camera are combined, for example VIO/SLAM. I think robotics is a common use case for oak-d, where then additional AI features are applied.
Btw: I got one of the early oak-d kickstarter devices with calibration for only two of the three cameras. So some spec-intrinsic/extrinsics for all devices would also be nice. Perhaps there could be a collection here on github?
The text was updated successfully, but these errors were encountered: