Kotonki: Agricultural Vehicle Built For Customization

Agriculture on any scale involves many tasks that require lifting, hauling, pushing, and pulling. On many modern farms, these tasks are often done using an array of specialized (and expensive) equipment. This puts many small-scale farmers, especially those in developing countries, under significant financial pressure. These challenges led a South African engineering firm to develop the Kotonki, a low-cost hydraulically powered utility vehicle that can be customized for a wide variety of use cases. Video after the break.

The name Kotonki is derived from the Setswana phrase for a donkey kart. It is in essence a self-propelled hydraulic power pack, capable of hauling 1 ton of anything that can fit on its load bed. It comes in front-wheel drive or four-wheel drive versions, with each wheel individually driven by a hydraulic motor. The simple welded steel frame articulates around a double pivot, which allows it to keep all 4 wheels on the ground over any terrain. At a max speed of 10 km/h it won’t win any races, but neither would most other agricultural vehicles. The Kotonki is built mostly using off-the-shelf components and is powered by a common 12HP Honda engine. In the world of DRM agricultural equipment, this makes for simple repairs, low running costs, and easy customization for the task at hand. This can include mounting log splitters, water pumps, lifting beds, or anything else that can be driven by its hydraulic and rotary PTOs (Power Take-Off).

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Computer Vision Extracts Lightning From Footage

Lightning is one of the more mysterious and fascinating phenomenon on the planet. Extremely powerful, but each strike on average only has enough energy to power an incandescent bulb for an hour. The exact mechanism that starts a lightning strike is still not well understood. Yet it happens 45 times per second somewhere on the planet. While we may not gain a deeper scientific appreciation of lightning anytime soon, but we can capture it in various photography thanks to this project which leverages computer vision machine learning to pull out the best frames of lightning.

The project’s creator, [Liam], built this as a tool for stormchasers and photographers so that they can film large amounts of time and not have to go back through their footage manually to pull out the frames with lightning strikes. The project borrows from a similar project, but this one adds Python 3 capabilities and runs on a tiny netbook for more easy field deployment. It uses OpenCV for object recognition, using video files as the source data, and features different modes to recognize different types of lightning.

The software is free and open source, and releases are supported for both Windows and Linux. So far, [Liam] has been able to capture all kinds of electrical atmospheric phenomenon with it including lightning, red sprites, and elves. We don’t see too many projects involving lightning around here, partly because humans can only generate a fraction of the voltage potential needed for the average lightning strike.

A 3D-printed device labelled "BlixTerm" plugged into the back of a Commodore PET

BlixTerm Brings Full-Speed YouTube Video To The Commodore PET

If you’ve ever used a home computer from the late 1970s or early 1980s, you’ll no doubt be familiar with the slow speed of their user interfaces. Even listing the contents of a BASIC program from RAM could take several seconds, with the screen updating one line at a time. Video games were completely optimized for speed, but could still handle just a few slowly-moving objects at the same time. Clearly, playing anything resembling full-motion video on hardware from that era would be absolutely impossible – or so you might think.

In fact, [Thorbjörn Jemander] has managed to persuade a Commodore PET to play YouTube videos at a completely reasonable 30 frames per second. He describes the process of designing the “BlixTerm” hardware and software in his video (embedded below), along with lots of useful information on how to push digital systems to their absolute limits.

A video of a drifting car, as rendered by a Commodore PET displayNaturally, the PET needs a bit of assistance from modern hardware, in this case a Raspberry Pi Zero 2 W hooked up to the “User” expansion port. The Pi connects to YouTube through WiFi and loads the requested video, then downconverts it to a 640×200 grayscale stream and transforms each frame to an 80×25 grid of characters, using those from the PET’s ROM that most closely resemble the pattern needed.

While it took quite some effort to squeeze enough performance out of the Pi to do all of this in real time, the trickiest bit was getting the resulting character stream into the PET’s video memory fast enough. To do this, [Thorbjörn] designed a special interface card with 2 KB of dual-port SRAM, which enabled the Pi to store its video frames as soon as they were ready on one side, and the PET to load them at its own pace from the other side. With just sixteen microseconds available to process each byte, the PET’s CPU can execute only four or five machine code instructions; barely enough to load and store a single character and jump to the next memory address.

The end result, as you can see in the video, is really impressive. Even within the constraints of the Commodore character set, the resulting image is clearly recognizable, while the frame rate seems to defy the hardware’s limitations.

If you’re a Commodore aficionado and wondering what the hell that weird PET 600 model is all about, [Thorbjörn] made a video about that too; it’s a rebadged 8296 aimed at the Swedish market. We’ve actually seen a project to generate live video on the PET before, although at a much lower frame rate. Thanks for the tip, [Keith Olson]!

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Converting A Sigma Lens To Canon, Digital Functionality Included

These days, camera lenses aren’t just simple bits of glass in sliding metal or plastic housings. They’ve often got a whole bunch of electronics built in as well. [Dan K] had just such a lens from Sigma, but wanted to get it working fully with a camera using the Canon EF lens fitting. Hacking ensued.

The lens in question was a Sigma 15-30mm f/3.5-4.5 EX DG, built to work with a Sigma camera using the SA mount. As it turns out, the SA mount is actually based on the Canon EF mount, using the same communications methods and having a similar contact block. However, it uses a mechanically different mounting bayonet, making the two incompatible.

[Dan] sourced a damaged EF lens to provide its mount, and modified it on a lathe to suit the Sigma lens. A short length of ribbon cable was then used to connect the lens’s PCB to the EF mount’s contacts. When carefully put back together, the lens worked perfectly, with functional auto-focus and all.

It goes to show that a little research can reveal possibilities for hacking that we might otherwise have missed. [Dan] was able to get his lens up and running on a new camera, and has taken many wonderful pictures with it since.

We’ve seen some great lens hacks over the years, from 3D printed adapters to anamorphic adapters that create beautiful results. If you’ve got your own mad camera hacks brewing up, drop us a line!

Hackaday Prize 2022: MasterPi Is A Capable Robot With Fancy Wheels

When it comes to building a mobile robot, often maneuverability is more important than outright speed. The MasterPi robot demonstrates this well, using fancy wheels to help it slide and skate in any direction needed.

Four DC gear-motors are fitted to a metal chassis, each one driving a mecanum wheel. These are special wheels with rollers fitted around their circumference at an angle that allows the robot to move in all directions and rotate in various ways depending on how each wheel is driven.

On top of this highly maneuverable chassis is placed a 5-degree-of-freedom robotic arm. The robot also gets a ultrasonic sensor for avoiding objects, as well as a camera for line-following duties. The camera also allows the robot to pick up blocks and identify their color, and it can then sort them into boxes. It’s all powered by a Raspberry Pi, running a bunch of Python code to make everything happen.

It’s a neat project that shows off just how capable a robot can be with some smart design choices and modern computing hardware on board. We’ve seen some other smart block sorters before, too. Continue reading “Hackaday Prize 2022: MasterPi Is A Capable Robot With Fancy Wheels”

Unraveling The Hackaday Podcast Hidden Message

When Elliot and I record the raw audio for the weekly podcast, it’s not unusual for us to spend the better part of two hours meandering from topic to topic. During one of these extended gab sessions, we wondered if it would be possible to embed a digital signal into the podcast in such a way that it could be decoded by the listener. Of course, storing and transmitting data via sound is nothing new — but the podcast format itself introduced some level of uncertainty.

Would the encoded sound survive the compression into MP3? Would the syndication service that distributes the file, or the various clients listeners will use to play it back, muddy the waters even further? Was it possible that the whole episode would get flagged somewhere along the line as malicious? After a bit of wild speculation, the conversation moved on to some other topic, and the idea was left to stew on one of our infinite number of back burners.

That is, until Elliot went on vacation a couple weeks back. In place of a regular episode, we agreed that I’d try my hand at putting together a special edition that consisted of pre-recorded segments from several of the Hackaday contributors. We reasoned this simplified approach would make it easier for me to edit, or to look at it another way, harder for me to screw up. For the first time, this gave me the chance to personally oversee the recording, production, and distribution of an episode. That, and the fact that my boss was out of town, made it the perfect opportunity to try and craft a hidden message for the Hackaday community to discover.

I’m now happy to announce that, eleven days after the EMF Camp Special Edition episode was released, ferryman became the first to figure out all the steps and get to the final message. As you read this, a coveted Hackaday Podcast t-shirt is already being dispatched to their location.

As there’s no longer any competition to see who gets there first, I thought it would be a good time to go over how the message was prepared, and document some interesting observations I made during the experiment.

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Hackaday Podcast 175: Moonrocks And Cockroach Chyme, A Raspberry Pi IPad, And A Retro-Respectful Tape Deck

Join Editor-in-Chief Elliot Williams and Assignments Editor Kristina Panos as we cuss and discuss all the gnarliest hacks from the past week. We kick off this episode with a gentle reminder that the Odd Inputs and Peculiar Peripherals Contest ends this Monday, July 4th, at 8:30 AM PDT. We’ve seen a ton of cool entries so far, including a new version of [Peter Lyons]’ Squeezebox keyboard that we’re itching to write up for the blog.

In other contest news, the Round 2 winners of the Reuse, Recycle, Revamp challenge of the 2022 Hackaday Prize have been announced. Elliot is super stoked about [Jason Knight]’s open-source recycled skateboard deck-making apparatus, and Kristina wishes she had the time and money to build some of the fundamental Precious Plastic machines.

Elliot managed to stump Kristina with this week’s What’s That Sound, though she probably should have made a semi-educated guess. From there, it’s on to missing moon rocks and the word of the day before we get into a handful of contest entries, including a mechanical keyboard to end all mechanical keyboards.

This really just scratches the surface of this week’s show, which includes some new hardware stuffed into old, as well as modern implementations of old technology. And in case you didn’t get enough of Kristina’s childhood memoirs, she goes a bit deeper into the teddy bears and telephones rooms of her memory palace.

Direct download, record it to tape, and play it on your boombox.

Check out the links below if you want to follow along, and as always, tell us what you think about this episode in the comments!

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