Hackaday Links: June 14, 2020

June 14, 2020 by Dan Maloney 17 Comments

You say you want to go to Mars, but the vanishingly thin atmosphere, the toxic and corrosive soil, the bitter cold, the deadly radiation that sleets down constantly, and the long, perilous journey that you probably won’t return from has turned you off a little. Fear not, because there’s still a way for you to get at least part of you to Mars: your intelligence. Curiosity, the Mars rover that’s on the eighth year of its 90-day mission, is completely remote-controlled, and NASA would like to add some self-driving capabilities to it. Which is why they’re asking for human help in classifying thousands of images of the Martian surface. By annotating images and pointing out what looks like soil and what looks like rock, you’ll be training an algorithm that one day might be sent up to the rover. If you’ve got the time, give it a shot — it seems a better use of time than training our eventual AI overlords.

We got a tip this week that ASTM, the international standards organization, has made its collection of standards for testing PPE available to the public. With titles like “Standard Test Method for Resistance of Medical Face Masks to Penetration by Synthetic Blood (Horizontal Projection of Fixed Volume at a Known Velocity)”, it seems like the standards body wants to make sure that that homebrew PPE gets tested properly before being put into service. The timing of this release is fortuitous since this week’s Hack Chat features Hiram Gay and Lex Kravitz, colleagues from the Washington University School of Medicine who will talk about what they did to test a respirator made from a full-face snorkel mask.

There’s little doubt that Lego played a huge part in the development of many engineers, and many of us never really put them away for good. We still pull them out occasionally, for fun or even for work, especially the Technic parts, which make a great prototyping system. But what if you need a Technic piece that you don’t have, or one that never existed in the first place? Easy — design and print your own custom Technic pieces. Lego Part Designer is a web app that breaks Technic parts down into five possible blocks, and lets you combine them as you see fit. We doubt that most FDM printers can deal with the fine tolerances needed for that satisfying Lego fit, but good enough might be all you need to get a design working.

Chances are pretty good that you’ve participated in more than a few video conferencing sessions lately, and if you’re anything like us you’ve found the experience somewhat lacking. The standard UI, with everyone in the conference organized in orderly rows and columns, reminds us of either a police line-up or the opening of The Brady Bunch, neither of which is particularly appealing. The paradigm could use a little rethinking, which is what Laptops in Space aims to do. By putting each participant’s video feed in a virtual laptop and letting them float in space, you’re supposed to have a more organic meeting experience. There’s a tweet with a short clip, or you can try it yourself. We’re not sure how we feel about it yet, but we’re glad someone is at least trying something new in this space.

And finally, if you’re in need of a primer on charlieplexing, or perhaps just need to brush up on the topic, [pileofstuff] has just released a video that might be just what you need. He explains the tri-state logic LED multiplexing method in detail, and even goes into some alternate uses, like using optocouplers to drive higher loads. We like his style — informal, but with a good level of detail that serves as a jumping-off point for further exploration.

Autonomous Sentry Gun Packs A Punch And A Ton Of Build Tips

June 10, 2020 by Dan Maloney 17 Comments

What has dual compressed-air cannons, 500 roll-on deodorant balls, and a machine-learning brain with a bad attitude? We didn’t know either, until [Leo Fernekes] dropped this video on his autonomous robot sentry gun and saw it in action for ourselves.

Now, we’ve seen tons of sentry guns on these pages before, shooting everything from water to various forms of Nerf. And plenty of those builds have used some form of machine vision to aim the gun onto the target. So while it might appear that [Leo]’s plowing old ground here, this build is chock full of interesting tips and tricks.

It started when [Leo] saw a video on TensorFlow basics from our friend [Edje Electronics], which gave him the boost needed to jump into an AI project. The controller he ended up with looks for humans in the scene and slews the turret onto target, where the air cannons can do their thing. The hefty ammo is propelled by compressed air, which is dumped into the chamber using a solenoid valve with an interesting driver that maximizes the speed at which it opens. Style points go to the bacteriophage T4-inspired design, and to the sequence starting at 1:34 which reminded us of the factory scene from RoboCop.

[Leo] really put a ton of work into this project, and the results show. He is hoping to get an art gallery or museum to show it as an interactive piece to comment on one possible robot-human future, presumably after getting guests to sign a release. Whatever happens to it, the robot looks great and [Leo] learned a lot from it, as did we.

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Machine Vision Keeps Track Of Grubby Hands

April 7, 2020 by Dan Maloney 4 Comments

Can you remember everything you’ve touched in a given day? If you’re being honest, the answer is, “Probably not.” We humans are a tactile species, with an outsized proportion of both our motor and sensory nerves sent directly to our hands. We interact with the world through our hands, and unfortunately that may mean inadvertently spreading disease.

[Nick Bild] has a potential solution: a machine-vision system called Deep Clean, which monitors a scene and records anything in it that has been touched. [Nick]’s system uses Jetson Xavier and a stereo camera to detect depth in a scene; he built his camera from a pair of Raspberry Pi cams and a Pi 3B+, but other depth cameras like a Kinect could probably do the job. The idea is to watch the scene for human hands — OpenPose is the tool he chose for that job — and correlate their depth in the scene with the depth of objects. Touch a doorknob or a light switch, and a marker is left on the scene. The idea would be that a cleaning crew would be able to look at the scene to determine which areas need extra attention. We can think of plenty of applications that extend beyond the current crisis, as the ability to map areas that have been touched seems to be generally useful.

[Nick] has been getting some mileage out of that Xavier lately — he’s used it to build an AI umpire and shades that help you find lost stuff. Who knows what else he’ll find to do with them during this time of confinement?

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Silicone And AI Power This Prayerful Robotic Intercessor

March 25, 2020 by Dan Maloney 27 Comments

Even in a world that is as currently far off the rails as this one is, we’re going to go out on a limb and say that this machine learning, servo-powered prayer bot is going to be the strangest thing you see today. We’re happy to be wrong about that, though, and if we are, please send links.

“The Prayer,” as [Diemut Strebe]’s work is called, may look strange, but it’s another in a string of pieces by various artists that explores just what it means to be human at a time when machines are blurring the line between them and us. The hardware is straightforward: a silicone rubber representation of a human nasopharyngeal cavity, servos for moving the lips, and a speaker to create the vocals. Those are generated by a machine-learning algorithm that was trained against the sacred texts of many of the world’s major religions, including the Christian Bible, the Koran, the Baghavad Gita, Taoist texts, and the Book of Mormon. The algorithm analyzes the structure of sacred verses and recreates random prayers and hymns using Amazon Polly that sound a lot like the real thing. That the lips move in synchrony with the ersatz devotions only adds to the otherworldliness of the piece. Watch it in action below.

We’ve featured several AI-based projects that poke at some interesting questions. This kinetic sculpture that uses machine learning to achieve balance comes to mind, while AI has even been employed in the search for spirits from the other side.

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Now You Can Be Big Brother Too, With A Raspberry Pi License Plate Reader

February 26, 2020 by Jenny List 61 Comments

If you are wowed by some of the abilities of a Tesla but can’t quite afford one, perhaps you can enhance your current ride with a few upgrades. This was what [Robert Lucian Chiriac] did with his Land Rover, to gain some insight into automotive machine vision he fitted it with a Raspberry Pi and camera with an automatic number plate recognition system.

This bracket should find a use in a few projects.

His exceptionally comprehensive write-up takes us through the entire process, from creating a rather useful set of 3D-printed brackets for a Pi and camera through deciding the combination of artificial intelligence software components required, to making the eventual decision to offload part of the processing to a cloud service through a 4G mobile phone link. In this he used Cortex, a system designed for easy deployment of machine learning models, which he is very impressed with.

The result is a camera in his car that identifies and reads the plates on the vehicles around it. Which in a way has something of the Big Brother about it, but in another way points to a future in which ever more accessible AI applications self-contained without a cloud service become possible that aren’t quite so sinister. It’s an inevitable progression whose privacy questions may go beyond a Hackaday piece, but it’s also a fascinating area of our remit that should be available at our level.

You can see the system in action in the video below the break, as well as find the code in his GitHub repository.

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New Contest: Train All The Things

January 21, 2020 by Mike Szczys 8 Comments

The old way was to write clever code that could handle every possible outcome. But what if you don’t know exactly what your inputs will look like, or just need a faster route to the final results? The answer is Machine Learning, and we want you to give it a try during the Train All the Things contest!

It’s hard to find a more buzz-worthy term than Artificial Intelligence. Right now, where the rubber hits the road in AI is Machine Learning and it’s never been so easy to get your feet wet in this realm.

From an 8-bit microcontroller to common single-board computers, you can do cool things like object recognition or color classification quite easily. Grab a beefier processor, dedicated ASIC, or lean heavily into the power of the cloud and you can do much more, like facial identification and gesture recognition. But the sky’s the limit. A big part of this contest is that we want everyone to get inspired by what you manage to pull off.

Yes, We Do Want to See Your ML “Hello World” Too!

Wait, wait, come back here. Have we already scared you off? Don’t read AI or ML and assume it’s not for you. We’ve included a category for “Artificial Intelligence Blinky” — your first attempt at doing something cool.

Need something simple to get you excited? How about Machine Learning on an ATtiny85 to sort Skittles candy by color? That uses just one color sensor for a quick and easy way to harvest data that forms a training set. But you could also climb up the ladder just a bit and make yourself a camera-based LEGO sorter or using an IMU in a magic wand to detect which spell you’re casting. Need more scientific inspiration? We’re hoping someday someone will build a training set that classifies microscope shots of micrometeorites. But we’d be equally excited with projects that tackle robot locomotion, natural language, and all the other wild ideas you can come up with.

Our guess is you don’t really need prizes to get excited about this one… most people have been itching for a reason to try out machine learning for quite some time. But we do have $100 Tindie gift certificates for the most interesting entry in each of the four contest categories: ML on the edge, ML on the gateway, AI blinky, and ML in the cloud.

Get started on your entry. The Train All The Things contest is sponsored by Digi-Key and runs until April 7th.

Hackaday Links: December 29, 2019

December 29, 2019 by Dan Maloney 25 Comments

The retrocomputing crowd will go to great lengths to recreate the computers of yesteryear, and no matter which species of computer is being restored, getting it just right is a badge of honor in the community. The case and keyboard obviously playing a big part in that look, so when a crowdfunding campaign to create new keycaps for the C64 was announced, Commodore fans jumped to fund it. Sadly, more than four years later, the promised keycaps haven’t been delivered. One disappointed backer, Jim Drew, decided he was sick of waiting, so he delved into the world of keycaps injection molding and started his own competing campaign. Jim details his adventures in his ~~Kickstarter~~ Indiegogo campaign, which makes for good reading even if you’re not into Commodore refurbishment. Here’s hoping Jim has better luck than the competition did.

Looking for anonymity in our increasingly surveilled world? You’re not alone, and in fact, we predict facial recognition spoofing products and methods will be a growth industry in the new decade. Aside from the obvious – and often illegal – approach of wearing a mask that blocks most of the features machine learning algorithms use to quantify your face, one now has another option, in the form of a colorful pattern that makes you invisible to the YOLOv2 algorithm. The pattern, which looks like a soft-focus crowd scene rendered in Mardi Gras colors, won’t make the algorithm think you’re someone else, but it will prevent you from being classified as a person. It won’t work with any other AI algorithm, but it’s still an interesting phenomenon.

We saw a great hack come this week about using an RTL-SDR to track down a water leak. Clayton’s water bill suddenly skyrocketed, and he wanted to track down the source. Luckily, his water meter uses the encoder receive-transmit (ERT) protocol on the 900 MHz ISM band to report his usage, so he threw an SDR dongle and rtlamr at the problem. After logging his data, massaging it a bit with some Python code, and graphing water consumption over time, he found that water was being used even when nobody was home. That helped him find the culprit – leaky flap valves in the toilets resulting in a slow drip that ran up the bill. There were probably other ways to attack the problem, but we like this approach just fine.

Are your flex PCBs making you cry? Friend of Hackaday Drew Fustini sent us a tip on teardrop pads to reduce the mechanical stress on traces when the board flexes. The trouble is that KiCad can’t natively create teardrop pads. Thankfully an action plugin makes teardrops a snap. Drew goes into a bit of detail on how the plugin works and shows the results of some test PCBs he made with them. It’s a nice trick to keep in mind for your flexible design work.