Footprint Projection Calibration

I finally finished the LiDAR boresight-camera calibration, it took much longer than I expected, but at least now I'm fairly savvy with OpenCV programming.

First I had to extract the silhouettes of the LiDAR footprints from the IR images I took of them a few weeks ago, then I had OpenCV determine their centroids and print them out on console.  This took a few tries to get right, as the program I wrote only extracted the largest silhouette from a threshold-filtered image, and some of the images required a lot of noise filtering while others had a weak footprint.  From the centroids I was able to determine both the line along which the LiDAR footprint will travel and the mounting error angle between the camera and LiDAR boresight.


The mounting error between the camera and LiDAR turned out to be a little less than 5 degrees after tossing the evident outliers.  This is fine for my purposes but would be a problem if MARCO needed to acquire a target from further than 10 meters or so.

To summarize, this whole calibration process allows MARCO to place the LiDAR footprint exactly on any image it takes, without seeing the actual footprint, given only the distance measurement from the LiDAR.  This is useful for determining whether MARCO is making LiDAR contact with the target, which is important for just about every stage of target acquisition.

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