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Correct inclination of image based on gyroscope #11
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Use topic: |
https://docs.px4.io/v1.9.0/en/config/flight_controller_orientation.html |
Basic algorithm is ready. Depending on the image type that we feed into the neural network, if we can use typical image types, we could integrate Python Image Library which has an easy built-in image rotation function. |
I am not sure that this means that the PX4 outputs yaw, pitch and roll. These pages discusses how to configure the orientation of the FC, not output.
Nice! The image is initially a ros image message, but can easily be converted to a opencv type with cv bridge. |
I will do it from now on. |
Perhaps a note on how to find relevant mavros topics, since this might not be exactly the one we want. The docs are out of date. I.e. the topics there still exist, but others exist too. The best way to find the topic you are looking for is to run mavros with either a simulator or the FC on the pi and look at the available topics with |
We have the following problems:
The Mavros state is
@hflemmen Did I do something wrong? |
First of all, make sure that there is an connection to the FC, i.e. that it is connected(and powered) and receiving mavlink hearbeats. If not, then you can check if LOG_DISARMED is set, that LOG_BACKEND_TYPE is at least set to mavlink and the other logging parameters.
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Okay so it is connected properly but I still do not receive any signal. Where are the log files located? |
Which log files do you mean? I think you can get the one from the FC through QGC. Not sure about the ROS ones. Perhaps somewhere in The log parameters have to be set so that the FC will send the relevant data. Sending data over the serial link is implemented in the same way as logging. |
In the simulator I get some data on(amongs others):
I guess first thing to try is to see if one of the first two can be decomposed into giving the inclination in roll direction. If not we may need to calculate it from one of the last two. |
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To make the human pose estimation more robust to rotations, we can transform the image to what will in the image frame be zero-rotation. We can get the rotation from the ardupilot EKF2.
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