Extended Kalman filter

 I'm trying to implement the Extended Kalman filter from the robot_localization package by clearpath, and I finally configured the launch file and the yaml file that holds all of the parameters. It turns out that all I had to do is to actually list the topics in the yaml file and voila! I have a readout of the pose estimate with covariance. However it seems that when I run the ekf noe along with all the other stuff the serial connection has a problem. At least the robot doesn't respond to the move commands anymore.

I'm honestly really tired of the serial problems as it's preventing me from working on the more interesting stuff like SLAM.

Here's a list of stuff I would like to work better:

PID. Currently I'm just using proportional control and it is very smooth. When I try to tune the PID controller better it usually ends up kinda jittery. So if this was better the error between the set velocity and the actual velocity would be less, which is also beneficial for the ekf. Because then I could use the control vel as an input. And enable that parameter to be used.

EKF. For some reason running this makes the robot irresponsive.

SLAM. I tried making a map of my house by driving the robot around, but there was an error and the map didn't work and it didn't show up in Rviz as I wanted.

Kinect: I'm having trouble with the depth camera and the stream in general. It seems that there isn't enough bandwidth on the USB bus if that makes any sense. It works fine on the pc, but the raspberry pi really struggles for some reason. Am I actually running into a resource limitation or am I just doing this in a really stupid way?

In any case, I finally finished my course on Data Structures and Algorithms and can now get back into working on this. uggghhhhhhhh. just do the thing!

On a happier note, I want to try loading my urdf model into Gazeebo. I think that could be fun, because I could assume that in a perfect world I wouldn't have hardware problems and could just drive the robot around.

Another thing I could start doing is contributing to open source communities.