What Do Bertlmann’s Socks Mean To The Nature Of Reality?

November 11, 2015 by Will Sweatman 41 Comments

One can be reasonably certain that when the title of an article includes the phrase “The Nature of Reality”, thought provoking words must surely lie ahead. But when that same title seems to inquire about a gentleman’s socks, coupled with an image of said gentleman’s socks which happen to be mismatched and reflect very loud colors , one might be moved in a direction which suggests the article is not of a serious nature. Perhaps even some sort of parody.

It is my hope that you will be pleasantly surprised with the subtle genius of Irish physicist [John Bell] and his use of socks, washing machines, and a little math to show how we can test one of quantum physic’s most fundamental properties. A property that does indeed reside in the very nature of the reality we are a part of. Few people can say they understand the Bell Inequality down to its most fundamental level. Give me a little of your time, and you will be counted among these few.

Continue reading “What Do Bertlmann’s Socks Mean To The Nature Of Reality?” →

Video With Sensor Data Overlay Via Arduino Mega

November 11, 2015 by Brandon Dunson 17 Comments

If you haven’t been paying attention, big wheel trikes are a thing. There are motor driven versions as well as OG pedal pushing types . [Flux Axiom] is of the OG (you only get one link, now its on you) flavor and has written an instructable that shows how to achieve some nice looking on screen data that he syncs up with the video for a professional looking finished product which you can see in the video after the break.

[Flux Axiom] is using an Arduino Mega in his setup along with a cornucopia of sensors and all their data is being logged onto an SD card. All the code used in his setup is available in his GitHub repository. [Flux Axiom] was also nice enough to include the calibration process he used for the sensors which is also located in the GitHub download.

Sadly [Flux Axiom] uses freedom hating software for combining the video and data, Race Render 3 is his current solution and he is pleased with the results. Leave it in the comments if you have an open source solution for combining the video and data that we can offer him as a replacement.

Edit: Correct spelling of handle.

Continue reading “Video With Sensor Data Overlay Via Arduino Mega” →

Drones Are Getting A Lot Smarter

November 11, 2015 by James Hobson 49 Comments

[DJI], everyone’s favorite — but very expensive — drone company just announced the Manifold — an extremely capable high performance embedded computer for the future of aerial platforms. And guess what? It runs Ubuntu.

The unit features a quad-core ARM Cortex A-15 processor with an NVIDIA Keplar-based GPU and runs Canonical’s Ubuntu OS with support for CUDA, OpenCV and ROS. The best part is it is compatible with third-party sensors allowing developers to really expand a drone’s toolkit. The benefit of having such a powerful computer on board means you can collect and analyze data in one shot, rather than relaying the raw output down to your control hub.

And because of the added processing power and the zippy GPU, drones using this device will have new artificial intelligence applications available, like machine-learning and computer vision — Yeah, drones are going to be able to recognize and track people; it’s only a matter of time.

We wonder what this will mean for FAA regulations…

Raspberry Pi-Powered Back To The Future Time Circuits

November 10, 2015 by Brian Benchoff 13 Comments

Here’s something that’s a little late to celebrate the fact that all the events in Back to the Future have happened in the past, but that’s what time machines are for, right? [Deater] created Pi-powered time circuits and a flux capacitor. He might not have a DeLorean, but he does have the equipment to turn a DeLorean into a cool car.

The ‘time circuits’ shown on-screen in Back to the Future actually weren’t very complex; the times were just cutouts with lights and gels; no real electronics wizardry necessary. Of course the BttF DeLorean has since been remodeled and refurbished with time circuits that look and act the part, and [Deater]’s time circuits have everything you would expect: a display of the destination, current, and last time, sound effects, numeric keypad, flux capacitor, and a speedometer.

While it doesn’t simulate the time circuits from the movie exactly, that’s not necessarily a bad thing. The movie time circuits were colored gels, and wouldn’t exactly be practical for a Raspberry Pi-based prop. It’s a great build, and one that would look great in either a ’98 Nissan Altima or a DeLorean

Continue reading “Raspberry Pi-Powered Back To The Future Time Circuits” →

Analog Clocks Play Their Own Beat

November 10, 2015 by Mike Szczys 10 Comments

Play the demo video below and try not to let the rhythm worm its way into your brain. What you’re hearing is the sound of a bunch of clocks, amplified. None of them are keeping wall time, but all of them are playing together.

[Gijs] makes crazy musical instruments. He doesn’t give us much more than a video and a couple schematics for this project, so this one’s still a bit of an enigma, but here’s what we’ve put together.

The video looks like eight identical version of the same module. The input takes a voltage and converts the rising and falling edges into pulses to drive the coil of an el-cheapo clock. The LEDs pulse as the poles of the clock switch to the incoming beats. The output comes from an amplified piezo sensor stuck on the back of each clock. That is, what you’re hearing is each clock ticking, but amplified. And if you watch the dials spin, it doesn’t look like any of them are telling time.

So far so good, and it matches up with the schematic. But what’s up with that switch on the front? It doesn’t show up anywhere.

And what’s driving the show? [Gijs] tantalizes us with a master clock module (on the same page) that looks like it does keep time, and outputs subdivisions thereof. But that would be too slow to be what’s used in the video. Has he swapped the crystal to make it run faster? It’s a mystery.

Of course, we’d expect no less from the man who mics up a kitchen timer or a gear motor and adds them to his synthesizer rack. We’ve covered a bunch more of [Gijs]’s work in the past, from his video mixers to this hard-drive turned synth oscillator, but this time he’s got us scratching our heads a bit, as well as tapping our feet.

Continue reading “Analog Clocks Play Their Own Beat” →

Nvidia Brings Computer Vision And Deep Learning To The Embedded World

November 10, 2015 by Brian Benchoff 101 Comments

Today, Nvidia announced their latest platform for advanced technology in autonomous machines. They’re calling it the Jetson TX1, and it puts modern GPU hardware in a small and power efficient module. Why would anyone want GPUs in an embedded format? It’s not about frames per second; instead, Nvidia is focusing on high performance computing tasks – specifically computer vision and classification – in a platform that uses under 10 Watts.

For the last several years, tiny credit card sized ARM computers have flooded the market. While these Raspberry Pis, BeagleBones, and router-based dev boards are great for running Linux, they’re not exactly very powerful. x86 boards also exist, but again, these are lowly Atoms and other Intel embedded processors. These aren’t the boards you want for computationally heavy tasks. There simply aren’t many options out there for high performance computing on low-power hardware.

Tiny ARM computers the size of a credit card have served us all well for general computing tasks, and this leads to the obvious question – what is the purpose of putting so much horsepower on such a small board. The answer, at least according to Nvidia, is drones, autonomous vehicles, and image classification.

Image classification is one of the most computationally intense tasks out there, but for autonomous robots, there’s no other way to tell the difference between a cyclist and a mailbox. To do this on an embedded platform, you either need to bring a powerful general purpose CPU that sucks down 60 or so Watts, or build a smaller, more efficient GPU-based solution that sips a meager 10 Watts.

Continue reading “Nvidia Brings Computer Vision And Deep Learning To The Embedded World” →

The Simplest Smart Glasses Concept

November 10, 2015 by Al Williams 76 Comments

Google Glass kind of came and went, leaving one significant addition to the English language. Even Google itself used the term “glasshole” for people who used the product in a creepy way. We can’t decide if wearing an obviously homemade set of glasses like the ones made by [Jordan Fung] are more creepy, give you more hacker cred, or just make you look like a Borg. Maybe some combination of all of those. While the cost and complexity of developing for Google Glass was certainly a barrier for hacking on that hardware, this project is just begging for you to build your own and run with the concept.

[Jordan’s] build, called Pedosa Glass, really is pretty respectable for a self-built set up. The Arduino Nano is a bit bulky, and the three push buttons take up some room, but it doesn’t kill the ability to mount them in a glasses form-factor. An FLCoS display lets you see the output of the software which [Jordan] is still developing. Right now features include a timer and a flashlight that uses the head-mounted white LED. Not much, we admit, but enough to prove out the hardware and the whole point would be to add software you wanted.

Admittedly, it isn’t exactly like Google Glass. Although both use FLCoS displays, Pedosa Glass uses a display meant for a camera viewfinder, so you don’t really see through it. Still, there might be some practical use for a little display mounted in your field of vision. The system will improve with a better CPU that is easier to connect to the network with sensors like an accelerometer — there’s plenty of room to iterate on this project. Then again, you do have an entire second ear piece to work with if you wanted to expand the system.

Check out the video demo after the break.

Continue reading “The Simplest Smart Glasses Concept” →