Tag:
machine learning
Smile, and the world smiles with you — or, in this case, a laser-cut flower running Android Things on a Raspberry Pi does. Expression Flower The aim of the Expression Flower is to “challenge the perception of what robotics can be while exploring the possibility for a whimsical experience that is engaging, natural, and fun.” Tl;dr: … Continue reading →
Let me start by stating that here in the UK, we call Waldo Wally. And as I’m writing this post at my desk at Pi Towers, Cambridge, I have taken the decision to refer to the red and white-clad fellow as Wally moving forward. Just so you know. There’s Waldo is a robot that finds Waldo … Continue reading →
Take a selfie, wait for the image to appear, and behold a cartoon version of yourself. Or, at least, behold a cartoon version of whatever the camera thought it saw. Welcome to Draw This by maker Dan Macnish. Dan has made code, instructions, and wiring diagrams available to help you bring this beguiling weirdery into … Continue reading →
Arduino is officially brilliant. It’s the perfect companion for your Raspberry Pi, opening up new possibilities for robotics, drones and all sorts of physical computing projects. In HackSpace magazine issue 8  we’re taking a look at what’s going on on planet Arduino, and how it can make our world better. This little board and its … Continue reading →
In an effort to create a robot that can teach itself to navigate different terrains, scientists at Arizona State University have built C-Turtle, a Raspberry Pi-powered autonomous cardboard robot with turtle flippers. This is excellent news for people who live in areas with landmines: C-Turtle is a great alternative to current landmine-clearing robots, since it … Continue reading →
Working here at Pi Towers, I’m always a little frustrated by not being able to share the huge number of commercial businesses’ embedded projects that use Raspberry Pis. (About a third of the Pis we sell go to businesses.) We don’t get to feature many of them on the blog; many organisations don’t want their work replicated by … Continue reading →
What you’re about to watch in the video below is a magnificently physical example of machine learning. Adam Vaughan is controlling an engine with an adaptive Extreme Learning Machine algorithm on his Pi, which predicts homogeneous charge compression ignition (HCCI – if you’re  a petrolhead, you won’t have to look that up on Wikipedia like I did … Continue reading →