Not content to leave things alone, [Nick Bild] has updated his nearly practical breadboard 6502 Vectron project once again by adding Tiny Basic and home tree automation. Instead of using an LCD module like last time, or his custom-built VGA output using 7400-series logic, [Nick] chose to go modern this time and implemented a VGA output using a TinyFPGA BX.
Tiny Basic was one of the first versions of Basic released after Bill Gates famous open letter to hobbyists in 1976. While Altair Basic was selling for $150, Tom Pittman wrote Tiny Basic for the 6800 and sold it for only $5 (don’t worry, Tom has since made it free to use). We got a kick out of browsing the Tiny Basic manual and learning that our serial number can be found on the paper tape leader, and that a Teletype will generally receive one more character, at least, after getting the X-OFF control signal.
In the video, you can see [Nick] running a short Basic program and operating his Christmas tree lights from the Vectron, although it’s only on-off control. He suggests that a PCB version is in the works, but he’s having trouble deciding when to quit adding features. That’s a conundrum we know all too well.
Continue reading “Vectron Adds Basic And Christmas Tree Control”
When it comes to machine learning algorithms, one’s thoughts do not naturally flow to the 6502, the processor that powered some of the machines in the first wave of the PC revolution. And one definitely does not think of gesture recognition running on a homebrew breadboard version of a 6502 machine, and yet that’s exactly what [Nick Bild] has accomplished.
Before anyone gets too worked up in the comments, we realize that [Nick]’s Vectron breadboard computer is getting a lot of help from other, more modern machines. He’s got a pair of Raspberry Pi 3s in the mix, one to capture and downscale images from a Pi cam, and one that interfaces to an Atari 2600 emulator and sends keypresses to control games based on the gestures seen by the camera. But the logic to convert gesture to control signals is all Vectron, and uses a k-nearest neighbor algorithm executed in 6502 assembly. Fifty gesture images are stored in ROM and act as references for the four known gesture classes: up, down, left, and right. When a match between the camera image and a gesture class is found, the corresponding keypress is sent to the game. The video below shows that the whole thing is pretty responsive.
In our original article on [Nick]’s Vectron breadboard computer, [Tom Nardi] said that “You won’t be playing Prince of Persia on it.” That may be true, but a machine learning system running on the Vectron is not too shabby either.
Continue reading “Machine Learning Algorithm Runs On A Breadboard 6502”