Way back in 2017, the R&D team (Elena Vazquez and James Coleman) at Zahner used a Kuka and an English wheel to develop a doubly curved surface. In short, they used grasshopper and kangaroo to extract the points and their direction from a surface, and then convert them to a 2d path for a Kuka and English wheel to follow. The results were beautiful.
In 2018 two researchers, Gabriella Rossi and Paul Nicholas pushed this even further. They basically added a Kinect, a network and AI so that the Kuka could learn and develop over time. Simply put. The results were, of course, more accurate. In theory, the more the Kuka wheels, the more accurate the results.
I’d like to test this theory and see how accurate we can really get using the point cloud/feedback loop setup.
I’ve attached an image from Zahner of what I’m trying to accomplish 1st.
Of course, I’m not asking for someone to make anything but I would appreciate it if someone could point me in the right direction. Essentially, I’m trying to take a doubly curved surface, subdivide and extract the points, find their direction and translate that to a 2d path for which to follow.
I’m familiar with grasshopper but obviously not an expert.
For this project, accuracy is more important than saving time and cutting corners.
Double Curve to 2D Path.gh (4.4 KB)