[Tony Liechty] has been having a few issues getting into CNC machining — starting with a simple router, he’s tripped over the usual beginners’ problems, you know, things like alignment of the design to the workpiece shape, axis clipping and workpiece/clamp collisions. He did the decent hacker thing, and turned to some other technologies to help out, and came up with a rather neat way of using machine vision with OpenCV to help preview the toolpath against an image of the workpiece in-situ (video, embedded below.)
ChArUco (a combined chessboard and ArUco marker pattern) boards taped to the machine rails were used to give OpenCV a reference of where points in space are with respect to the pattern field, enabling identification of pixel locations within the image of the rails. A homography transformation is then used to link the two side references to an image of the workpiece. This transformation allows the system to determine the physical location of any pixel from the workpiece image, which can then be overlaid with an image of the desired toolpath. Feedback from the user would then enable adjustment of the path, such as shifts, or rotates to be effected in order to counter any issue that can be seen. The reduction of ‘silly’ clamping, positioning and other such issues, means less time wasted and fewer materials in scrap bin, and that can only be a good thing.
[Tony] says this code and setup is just a demo of the concept, but such ‘rough’ code could well be the start of something great, we shall see. Checkout the realWorldGcodeSender GitHub if you want to play along at home!
We’ve seen a few uses of OpenCV for assisting with CNC applications, like this cool you draw it, i’ll cut it hack, and this method for using machine vision to zero-in a CNC mill onto the centre of a large hole.
