arduino

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Sunrise, Sunset, Repeat

August 25, 2020 by 5 Comments

Sunrises and sunsets hardly ever disappoint. Still, it’s difficult to justify waking up early enough to catch one, or to stop what you’re doing in the evening just to watch the dying light. If there’s one good thing about CCTV cameras, it’s that some of them are positioned to catch a lovely view of one of the two, and a great many of them aren’t locked down at all.

[Dries Depoorter] found a way to use some of the many unsecured CCTV cameras around the world for a beautiful reason: to constantly show the sun rising and setting. Here’s how it works: a pair of Raspberry Pi 3B + boards pull the video feeds and display the sunrise/sunset location and the local time on VFD displays using an Arduino Nano Every. There isn’t a whole lot of detail here, but you can probably get the gist from the high-quality pictures.

If you wanted to recreate this for yourself, we might know where you can find some nice CCTV camera candidates. Just look through this dystopian peephole.

Thanks for the tip, [Luke]!

Four Steppers Make A Four-Voice MIDI Instrument

August 15, 2020 by 17 Comments

Any owner of a budget 3D printer will tell you that they can be pretty noisy devices, due to their combinations of stepper motors and drives chosen for cost rather than quiet. But what if the noise were an asset, could the annoying stepper sound be used as a musical instrument? It’s a question [David Scholten] has answered with the Stepper Synth, a device that takes an Arduino Uno and four stepper motors to create a four-voice MIDI synthesiser.

Hardware-wise it’s as simple as you’d expect, a box with four stepper motors each with a red 3D-printed flag on its shaft to show rotation. Underneath there is the Arduino, plus a robot control shield and a set of stepper driver boards. On the software side it uses MIDI-over-serial, so as a Windows user his instructions for the host are for that operating system only. The Arduino makes use of the Arduino MIDI library, and he shares tips on disabling the unused motors to stop overheating.

You can hear it in action in the video below the break, and we’re surprised to say it doesn’t sound too bad. There’s something almost reminiscent of a church organ in there somewhere, it would be interesting to refine it with an acoustic enclosure of some kind.

This isn’t the first such instrument we’ve brought you, for a particularly impressive example take a look at the Floppotron.

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Odyssey Is A X86 Computer Packing An Arduino Along For The Trip

August 7, 2020 by 58 Comments

We love the simplicity of Arduino for focused tasks, we love how Raspberry Pi GPIO pins open a doorway to a wide world of peripherals, and we love the software ecosystem of Intel’s x86 instruction set. It’s great that some products manage to combine all of them together into a single compact package, and we welcome the recent addition of Seeed Studio’s Odyssey X86J4105.

[Ars Technica] recently looked one over and found it impressive from the perspective of a small networked computer, but they didn’t dig too deeply into the maker-friendly side of the product. We can look at the product documentation to see some interesting details. This board is larger than a Raspberry Pi, but its GPIO pins were laid out in exactly the same order as that on a Pi. Some HATs could plug right in, eliminating all the electrical integration leaving just the software issue of ARM vs x86. Tasks that are not suitable for CPU-controlled GPIO (such as generating reliable PWM) can be offloaded to an on-board Arduino-compatible microcontroller. It is built around the SAMD21 chip, similar to the Arduino MKR and Arduino Zero but the pinout does not appear to match any of the popular Arduino form factors.

The Odyssey is not the first x86 single board computer (SBC) to have GPIO pins and an onboard Arduino assistant. LattePanda for example has been executing that game plan (minus the Raspberry Pi pin layout) for the past few years. We’ve followed them since their Kickstarter origins and we’ve featured creative uses here and there. LattePanda’s current offerings are built around Intel CPUs ranging from Atom to Core m3. The Odyssey’s Celeron is roughly in the middle of that range, and the SAMD21 is more capable than the ATmega32U4 (Arduino Leonardo) on board a LattePanda. We always love seeing more options in a market for us to find the right tradeoff to match a given project, and we look forward to the epic journeys yet to come.

Generate Positivity With Machine Learning

August 6, 2020 by 4 Comments

Gesture recognition and machine learning are getting a lot of air time these days, as people understand them more and begin to develop methods to implement them on many different platforms. Of course this allows easier access to people who can make use of the new tools beyond strictly academic or business environments. For example, rollerblading down the streets of Atlanta with a gesture-recognizing, streaming TV that [nate.damen] wears over his head.

He’s known as [atltvhead] and the TV he wears has a functional LED screen on the front. The whole setup reminds us a little of Deep Thought. The screen can display various animations which are controlled through Twitch chat as he streams his journeys around town. He wanted to add a little more interaction to the animations though and simplify his user interface, so he set up a gesture-sensing sleeve which can augment the animations based on how he’s moving his arm. He uses an Arduino in the arm sensor as well as a Raspberry Pi in the backpack to tie it all together, and he goes deep in the weeds explaining how to use Tensorflow to recognize the gestures. The video linked below shows a lot of his training runs for the machine learning system he used as well.

[nate.damen] didn’t stop at the cheerful TV head either. He also wears a backpack that displays uplifting messages to people as he passes them by on his rollerblades, not wanting to leave out those who don’t get to see him coming. We think this is a great uplifting project, and the amount of work that went into getting the gesture recognition machine learning algorithm right is impressive on its own. If you’re new to Tensorflow, though, we have featured some projects that can do reliable object recognition using little more than a Raspberry Pi and a camera.

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Miles The Spider Robot

August 6, 2020 by 7 Comments

Who doesn’t love robotic spiders? Today’s biomimetic robot comes in the form of Miles, the quadruped spider robot from [_Robox].

Miles uses twelve servos to control its motion, three on each of its legs, and also includes a standard HC-SR04 ultrasonic distance sensor for some obstacle avoidance capabilities. Twelve servos can use quite a bit of power, so [_Robox_] had to power Miles with six LM7805 ICs to get sufficient current. [_Robox_] laser cut acrylic sheets for Miles’s body but mentions that 3D printing would work as well.

Miles uses inverse kinematics to get around, which we’ve seen in a previous project and is a pretty popular technique for controlling robotic motion. The Instructable is a little light on the details, but the source code is something to take a look at. In addition to simply moving around [_Robox_] developed code to make Miles dance, wave, and take a bow. That’s sure to be a hit at your next virtual show-and-tell.

By now you’re saying “wait, spiders have eight legs”, and of course you’re right. But that’s an awful lot of servos. Anyway, if you’d rather 3D print your four-legged spider, we have a suggestion.

Optimizing GIF Playback For Microcontrollers

August 3, 2020 by 15 Comments

Despite being cooked up by Compuserve back in the late 1980s, GIFs have seen a resurgence on the modern internet, mostly because they’re fun. However, all our small embedded systems are getting color screens these days, and they’d love to join in the party. [Larry Bank] has whipped up a solution for just that reason, letting embedded systems play back short animated GIFs with limited resources.

[Larry] does a great job of explaining how the GIF format works, using LZW compression and variable-length codes. He talks about how the design of the format presents challenges, particularly when working with microcontrollers. Despite this, the final code works well, and is able to work with most animated GIFs of the right dimensions and construction. 24K of RAM is required, and image width is limited to 320 pixels. Images can be loaded from flash, memory, or SD cards, and he notes that best performance is gained with a microcontroller with fast SPI for writing to screens quickly.

It’s a great piece of software that promises to add a lot of charm, or silliness, to microcontroller projects. It also simplifies the use of animations, which can now be designed on computers rather than by using onboard graphics libraries. GIF really is the format that never seems to die; we’ve featured cameras dedicated to the form before. Video after the break.

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Electrochemistry At Home

August 2, 2020 by 11 Comments

A few years ago, I needed a teeny, tiny potentiostat for my biosensor research. I found a ton of cool example projects on Hackaday and on HardwareX, but they didn’t quite fulfill exactly what I needed. As any of you would do in this type of situation, I decided to build my own device.

Now, we’ve talked about potentiostats before. These are the same devices used in commercial glucometers, so they are widely applicable to a number of biosensing applications. In my internet perusing, I stumbled upon a cool chip from Texas Instruments called the LMP91000 that initially appeared to do all the hard work for me. Unfortunately, there were a few features of the LMP91000 that were a bit limiting and didn’t quite give me the range of flexibility I required for my research. You see, electrochemistry works by biasing a set of electrodes at a given potential and subsequently driving a chemical reaction. The electron transfer is measured by the sensing electrode and converted to a voltage using a transimpedance amplifier (TIA). Commercial potentiostats can have voltage bias generators with microVolt resolution, but I only needed about ~1 mV or so. The problem was, the LMP91000 has a resolution of ~66 mV on a 3.3 V supply, mandating that I augment the LMP991000 with an external digital-to-analog converter (DAC) as others had done.

However, changing the internal reference of the LMP91000 with the DAC confounded the voltage measurements from the TIA, since the TIA is also referenced to the same internal zero as the voltage bias generator. This seemed like a problem other DIY solutions I came across should have mentioned, but I didn’t quite find any other papers describing this problem. After punching myself a little, I thought that maybe it was a bit more obvious to everyone else except me. It can be like that sometimes. Oh well, it was a somewhat easy fix that ended up making my little potentiostat even more capable than I had originally imagined.

I could have made a complete custom potentiostat circuit like a few other examples I stumbled upon, but the integrated aspect of the LMP91000 was a bit too much to pass up. My design needed to be as small as possible since I would eventually like to integrate the device into a wearable. I was using a SAMD21 microcontroller with a built-in DAC, therefore remedying the problem was a bit more convenient than I originally thought since I didn’t need an additional chip in my design.

I am definitely pretty happy with the results. My potentiostat, called KickStat, is about the size of a US quarter dollar with a ton of empty space that could be easily trimmed on my next board revision. I imagine this could be used as a subsystem in any number of larger designs like a glucometer, cellphone, or maybe even a smartwatch.

Check out all the open-source files on my research lab’s GitHub page. I hope my experience will be of assistance to the hacker community. Definitely a fun build and I hope you all get as much kick out of it as I did.