Update 3: first results with the EKF


I have some preliminar results with the Extended Kalman Filter and I loaded on youtube a short video in which you can see a comparison between the real robot pose (blue triangle), the red one is the pose measured and the green one is the estimated pose.
The model takes as input the steering angle and the velocity, both with a sin(t) noise overlapped. For now I’m using a very simple model with three state variables (x,y,theta) but I can do something better. For now, enjoy this video!


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