Adaptive DropCutter step-forward
The DropCutter strategy is probably the most simple algorithm for machining. It calculates the lowest possible position of the tool at various locations above the model. The path of the tool is usually split into parallel lines of movement. Since this strategy is simply based on sampling the surface of all cutter locations, the crucial parameter here is the “step-forward” – the distance between two points of calculation on one line.
Basically the chosen fixed sample rate is a trade-off between accuracy and the required time for calculating the toolpath.
The adaptive sample rate for the DropCutter strategy was inspired by a
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The code basically inserts points into the existing toolpath (starting with a fixed step-forward of 1/4 of the tool radius) as long as three consecutive points are not sufficiently flat. This recursion is terminated by a maximum recursion depth (currently 8), a minimum distance between adjacent points (currently 1/1000 of the tool radius) and a flatness deviance of 0.1% – this corresponds roughly to an angle of 2 degrees. This seems to generate a quite precise toolpath.
Performance-wise the adaptive DropCutter strategy takes just as much processing time as a fixed-step calculation grid (with a step-forward of 1/10 of the tool radius). Thus the precision around the interesting parts of the model is greatly increased, while performance does not suffer at all.
The screenshot at the top of this post visualizes this difference between a fixed-step DropCutter toolpath (upper line) and the new adaptive positioning. Have fun with it!