Like a lot of 16-year-olds, [Maxime Coutée] wanted an Oculus Rift. Unlike a lot of 16-year-olds, [Maxime] and friends [Gabriel] and [Jonas] built one themselves for about a hundred bucks and posted it on GitHub. We’ll admit that at 16 we weren’t throwing around words like quaternions and antiderivatives, so we were duly impressed.
Before you assume this is just a box to put a phone in like a Google Cardboard, take a look at the bill of materials: an Arduino Due, a 2K LCD screen, a Fresnel lens, and an accelerometer/gyro. The team notes that the screen is what will push the price unpredictably, but they got by for about a hundred euro. At the current exchange rate, if you add up all the parts, they went a little over $100, but they were still under $150 assuming you have a 3D printer to print the mechanical parts.
Macros are useful things. They allow one to execute a series of commands with a single keypress. There exists a wide variety of hardware and software solutions to create and use macros to improve your workflow, and now [Evan] has brought the open-source ManyKey into the fray, along with a build tutorial to boot.
The tutorial acts as a great introduction to ManyKey, as [Evan] walks through the construction of a macro keyboard designed to be operated by the feet. Based around the Arduino Leonardo and using off-the-shelf footswitches commonly used in guitar effects, it’s accessible while still hinting at the flexibility of the system. Macros are programmed into the keyboard through a Python app which communicates over serial, and configurations are saved into the Arduino’s onboard EEPROM. The ManyKey source is naturally available over at GitHub.
[Evan] tells us he uses his setup to run DJ software with his feet while his hands are busy on the turntables. That said, there’s all manner of other applications this could be used for. Efficiency is everything, and we love to see keyboard projects that aim to improve workflow with new ideas and custom builds – this shortcut keyboard makes a great example.
An Arduino and a data radio can make a great remote sensor node. Often in such situations, the hardware ends up installed somewhere hard to get to – be it in a light fitting, behind a wall, or secreted somewhere outdoors. Not places that you’d want to squeeze a cable repeatedly into while debugging.
Using the NRF24L01 chip with the Arduino is a popular choice to add wireless communications to a small project. By installing one of these radios on both the remote hardware and a local Arduino connected to the programming computer, it’s possible to remotely flash the Arduino without any physical contact whatsoever using Optiboot.
The writeup is comprehensive and covers both the required hardware setup for both ends of the operation as well as how to install the relevant bootloaders. If you’re already using the NRF24L01 in your projects, this could be the ideal solution to your programming woes. Perhaps you’re using a different platform though – like an Arduino on WiFi? Don’t worry – you can do OTA updates that way, too.
There are plenty of PC joysticks out there, but that didn’t stop [dizekat] from building his own. Most joysticks measure position mechanically using potentiometers or encoders. Only a few high-end models use Hall effect sensors. That’s the route [dizekat] took.
Hall effect sensors are non-contact devices which measure magnetic fields. They can be used to measure the position and orientation of a magnet. That’s exactly how [dizekat] is using a trio of sensors in his design. The core of the joystick is a universal joint from an old R/C car. The center section of the joint (called a spider) has two one millimeter thick disc magnets glued to it. The Hall sensors themselves are mounted in the universal itself. [Dizekat] used a small piece of a chopstick to hold the sensors in position while he found the zero point and glued them in. A third Hall effect sensor is used to measure a throttle stick positioned on the side of the box.
An Arduino micro reads the sensors and converts the analog signal to USB. The Arduino Joystick Library by [Matthew Heironimus] formats the data into something a PC can understand.
While this is definitely a rough work in progress, we’re excited by how much [dizekat] has accomplished with simple hand tools and glue. You don’t need a 3D printer, laser cutter, and a CNC to pull off an awesome hack!
At its heart is a modified Arduino Nano clone that draws a measured 608 nA from a CR2450N. From the specification of the cell he has calculated the 50 year maximum figure, as well as a possible 29 years for a CR2032 and 64 years for a CR2477. He does however note that this does not take self-discharge into account, but you can probably afford a new battery in a decade or so.
The Arduino clone carefully selected for its “P” version low-power processor has had its serial bridge IC removed to achieve this power consumption, as well as a voltage regulator and some discrete components. Interestingly he notes that the ATMega168P is even more frugal than its 328 cousin, so he’s used the former chip. A selection of internal flags are set for minimal power consumption, and the internal oscillator is selected to use as low a clock speed as possible. There is an Intersil ISL1208 low power RTC chip mounted on a piece of stripboard to provide the timing, and of course an LED to provide the essential birthday alert.
In a project, repetitive tasks that break the flow of development work are incredibly tiresome and even simple automation can make a world of difference. [Simon Merrett] ran into exactly this while testing different stepper motors in a strain-wave gear project. The system that drives the motor accepts G-Code, but he got fed up with the overhead needed just to make a stepper rotate for a bit on demand. His solution? A grbl man-in-the-middle jog pendant that consists of not much more than a rotary encoder and an Arduino Nano. The unit dutifully passes through any commands received from a host controller, but if the encoder knob is turned it sends custom G-Code allowing [Simon] to dial in a bit acceleration-controlled motor rotation on demand. A brief demo video is below, which gives an idea of how much easier it is to focus on the nuts-and-bolts end of hardware when some simple motor movement is just a knob twist away.
What do you do, when you need a random number in your programming? The chances are that you reach for your environment’s function to do the job, usually something like rand() or similar. This returns the required number, and you go happily on your way.
Except of course the reality isn’t quite that simple, and as many of you will know it all comes down to the level of randomness that you require. The simplest way to generate a random number in software is through a pseudo-random number generator, or PRNG. If you prefer to think in hardware terms, the most elementary PRNG is a shift register with a feedback loop from two of its cells through an XOR gate. While it provides a steady stream of bits it suffers from the fatal flaw that the stream is an endlessly repeating sequence rather than truly random. A PRNG is random enough to provide a level of chance in a computer game, but that predictability would make it entirely unsuitable to be used in cryptographic security for a financial transaction.
There is a handy way to deal with the PRNG predictability problem, and it lies in ensuring that its random number generation starts at a random point. Imagine the shift register in the previous paragraph being initialised with a random number rather than a string of zeros. This random point is referred to as the seed, and if a PRNG algorithm can be started with a seed derived from a truly unpredictable source, then its output becomes no longer predictable.
Selecting Unpredictable Seeds
Computer systems that use a PRNG will therefore often have some form of seed() function alongside their rand() function. Sometimes this will take a number as an argument allowing the user to provide their own random number, at other times they will take a random number from some source of their own. The Sinclair 8-bit home computers for example took their seed from a count of the number of TV frames since switch-on.
The Arduino Uno has a random() function that returns a random number from a PRNG, and as you might expect it also has a randomSeed() function to ensure that the PRNG is seeded with something that will underpin its randomness. All well and good, you might think, but sadly the Atmel processor on which it depends has no hardware entropy source from which to derive that seed. The user is left to search for a random number of their own, and sadly as we were alerted by a Twitter conversation between @scanlime and @cybergibbons, this is the point at which matters start to go awry. The documentation for randomSeed() suggests reading the random noise on an unused pin via analogRead(), and using that figure does not return anything like the required level of entropy. A very quick test using the Arduino Graph example yields a stream of readings from a pin, and aggregating several thousand of them into a spreadsheet shows an extremely narrow distribution. Clearly a better source is called for.
Noisy Hardware or a Jittery Clock
As a slightly old-school electronic engineer, my thoughts turn straight to a piece of hardware. Source a nice and noisy germanium diode, give it a couple of op-amps to amplify and filter the noise before feeding it to that Arduino pin. Maybe you were thinking about radioactive decay and Geiger counters at that point, or even bouncing balls. Unfortunately though, even if they scratch the urge to make an interesting piece of engineering, these pieces of hardware run the risk of becoming overcomplex and perhaps a bit messy.
The best of the suggestions in the Twitter thread brings us to the Arduino Entropy Library, which uses jitter in the microcontroller clock to generate truly random numbers that can be used as seeds. Lifting code from the library’s random number example gave us a continuous stream of numbers, and taking a thousand of them for the same spreadsheet treatment shows a much more even distribution. The library performs as it should, though it should be noted that it’s not a particularly fast way to generate a random number.
So should you ever need a truly random number in your Arduino sketch rather than one that appears random enough for some purposes, you now know that you can safely disregard the documentation for a random seed and use the entropy library instead. Of course this comes at the expense of adding an extra library to the overhead of your sketch, but if space is at a premium you still have the option of some form of hardware noise generator. Meanwhile perhaps it is time for the Arduino folks to re-appraise their documentation.