Where would the world be today without Pong, perhaps a lot less fun? For people like [Linker3000] the game is an inspiration toward teaching the next generation of hackers to build and play their own version using Micro:bits as controllers!
Aiming for doing all manner of diligence, [Linker3000] says the code can simply be uploaded to an Arduino — foregoing throwing together a circuit of your own — if you want to jump right into things. For the workshop environment, this setup uses composite video outputs — but this shouldn’t be an issue as most TVs still retain these inputs.
Once built — or sketch uploaded — the Micro:bit paddles can be connected to the ATmega328p and played like an old-school controller, but [Linker3000] has enabled Bluetooth control of the paddles’ A and B buttons via the Bitty app. Additionally — if wires really aren’t your thing and Bluetooth is too new-school for such an old game — a second Micro:bit can control the wired paddle using their built-in radio, provided they’re configured accordingly.
On top of Pong, there are also squash and soccer game modes! Check out the demo after the break.
If you’ve ever wanted to take a dive into and visualize a game’s code, this could be a seminal example in a literal sense. After twenty-one months of effort, the entire Pokemon Red game is now playable inside Minecraft.
[Mr. Squishy] is the mad genius behind this project, laboriously re-coding the game literally block by block. A texture pack is needed for the specific sprites, but otherwise it is playable without mods. It’s not immediately apparent when loading in to the level, but chip your way through the floor of the stadium and you are confronted by something awe-inspiring: sprawling constructions, like great soaring cliffs, comprising approximately 357,000 command blocks — equating to the same in lines of code. Every animation, tracked stat, attack and their effects, the various pokemon and their properties, and so on are rendered in the game’s physical space for you to wander through.
Beneath that are levels of maps, positional data, properties of those areas, NPCs, and a clever glitch that [Mr. Squishy] used to keep everything loaded at once.
Depending on which hemisphere of the Earth you’re currently reading this from, summer is finally starting to fight its way to the surface. For the more “green” of our readers, that can mean it’s time to start making plans for summer gardening. But as anyone who’s ever planted something edible can tell you, garden pests such as squirrels are fantastically effective at turning all your hard work into a wasteland. Finding ways to keep them away from your crops can be a full-time job, but luckily it’s a job nobody will mind if automation steals from humans.
[Peter Quinn] writes in to tell us about the elaborate lengths he is going to keep bushy-tailed marauders away from his tomatoes this year. Long term he plans on setting up a non-lethal sentry gun to scare them away, but before he can get to that point he needs to perfect the science of automatically targeting his prey. At the same time, he wants to train the system well enough that it won’t fire on humans or other animals such as cats and birds which might visit his garden.
A Raspberry Pi 3 with a cheap webcam is used to surveil the garden and detect motion. When frames containing motion are detected, they are forwarded to a laptop which has enough horsepower to handle the squirrel detection through Darknet YOLO. [Peter] recognizes this isn’t an ideal architecture for real-time targeting of a sentry turret, but it’s good enough for training the system.
Which incidentally is what [Peter] spends the most time explaining on the project’s Hackaday.io page. From the saga of getting the software environment up and running to determining how many pictures of squirrels in his yard he should provide the software for training, it’s an excellent case study in rolling your own image recognition system. After approximately 18 hours of training, he now has a system which is able to pick squirrels out from the foliage. The next step is hooking up the turret.
As [Marius Hornberger] was working in his woodshop, a thunderous bang suddenly rocked the space. A brief search revealed the blower for the dust collector had shifted several inches despite being stoutly fastened down. Turns out, the blower had blown itself up when one of the impeller fins came loose. Time to revise and build a bigger, better dust collector!
[Hornberger] is thorough in describing his process, the video series chronicles where he went astray in his original design and how he’s gone about improving on those elements. For instance, the original impeller had six fins which meant fewer points to bear the operating stresses as well as producing an occasionally uncomfortable drone. MDF wasn’t an ideal material choice here either, contributing to the failure of the part.
The typical hacker can never say no to more tools. And when it comes to clamps, one just can’t have enough of them. From holding small PCB’s to clamping together large sheets of plywood, you need a variety of sizes and quantities. So it would be pretty neat if we could just 3D print them whenever needed. [Mgx3d] has done that by designing 3D printable bar clamp jaws with a quick release mechanism that can be used with standard T-slot aluminum extrusion. This allows you to create ad-hoc bar clamps of any size and length quickly.
The design consists of two pieces – the jaw and its quick release lever, and does not require any additional parts or fasteners for assembly. Both pieces can be easily 3D printed without supports. The quick release lever is a simple eccentric cam design which locks the jaw in place by pushing down on the extrusion. The design is parametric and can be easily customized for different sizes, either in OpenSCAD or via the online customizer. The online customizer supports Misumi 15 mm and 20 mm extrusion, 1″ 1010-S and 20 mm 20-2020 from 80/20 Inc., 15 mm from OpenBeam and 10 mm from MicroRax. But it ought to be easy to create fresh designs in OpenSCAD. Check out the video after the break to see the bar-clamps in action.
Our bodies are not like LEGO blocks or computers because we cannot swap out our parts in the living room while watching television. Organ transplants and cosmetic surgery are currently our options for upgrades, repairs, and augments, but post-transplant therapy can be a lifelong commitment because of rejection. Elective surgery costs more than a NIB Millenium Falcon LEGO set. Laboratories have been improving the processes and associated treatments for decades but experimental labs and even home laboratories are getting in on the action as some creative minds take the stage. These folks aren’t performing surgeries, but they are expanding what is possible to for people to do and learn without a medical license.
One promising gateway to human building blocks is the decellularization and recellularization of organic material. Commercial scaffolds exist but they are expensive, so the average tinkerer isn’t going to be buying a few to play with over a holiday weekend.
Let’s explore what all this means. When something is decellularized, it means that the cells are removed, but the structure holding the cells in place remains. Recellularizing is the process where new cells are grown in that area. Decellularizing is like stripping a Hilton hotel down to the girders. The remaining structures are the ECM or the Extra Cellular Matrix, usually referred to as scaffolding. The structure has a shape but no functionality, like a stripped hotel. The scaffolding can be repopulated with new cells in the same way that our gutted hotel can be rebuilt as a factory, office building, or a hospital.
Alorium rolled out a new product late last year that caught our attention. The Sno (pronounced like “snow”) board is a tiny footprint Arduino board that you can see in the video below. By itself that isn’t that interesting, but the Sno also has an Altera/Intel Max 10 FPGA onboard. If you aren’t an FPGA user, don’t tune out yet, though, because while you can customize the FPGA in several ways, you don’t have to.
Like Alorium’s XLR8 product, the FPGA comes with preprogrammed functions and a matching Arduino API to use them. In particular, there are modules to do analog to digital conversion, servo control, operate NeoPixels, and do floating point math.