Most CNC workflows start with a 3D model, which is then passed to CAM software to be converted into the G-code language that CNC machines love and understand. G-code, however, is simple enough that rudimentary coding skills are all you need to start writing your very own programmatic CNC tool paths. Any language that can output plain text is fully capable of enabling you to directly control powerful motors and rapidly spinning blades.
[siemenc] shows us how to use Grasshopper – a visual node-based programming system for Rhino 3D – to output G-code that makes some interesting patterns and shapes in wood when fed to a ShopBot. Though the Rhino software is a bit expensive and thus is not too widely available, [siemenc] walks through some background, theory, and procedures that could be useful and inspirational no matter what software or programming language you’re using to create your bespoke G-code.
For links to code and related blog posts, plus more lovely pictures of intricately carved plywood, check out [siemenc]’s personal site as well.
[via Bantam Tools]
A plague of locusts descends on your garden, and suddenly you realize grasshoppers are very hard to catch. Grasshoppers are nature’s perfect collision avoidance system, and this is due to a unique visual system that includes neurons extending directly from the eye to the animal’s legs. For this Hackaday Prize entry – and as a research project for this summer at Backyard Brains, [Dieu My Nguyen] is studying the neuroscience of grasshopper vision with stabs and shocks.
We visited Backyard Brains about two years ago, and found three very interesting projects. The first was a project on optogenetics, or rewiring neurons so flies taste something sweet when they’re exposed to red light. The second was remote-controlled cockroaches. Number three will shock you: a device that allowed me to expand my megalomania by shocking people with the power of my mind. It’s not all fun and games, though. This grasshopper neuron probe will use the Backyard Brains SpikerBox to investigate when those neurons are activated in response to a stimuli.
The utility of looking at the common grasshopper to learn about collision and object avoidance may not be very apparent at first. The more you learn about neuroscience, the more apparent the biological connection to common computer vision tasks becomes. That makes this a great research project and an excellent entry into the Hackaday Prize.