Honey, I Shrunk The Arduino Core

April 5, 2021 by Bryan Cockfield 69 Comments

High-level programming languages do a great job of making a programmer’s job easier, but these languages often leave a lot of efficiency on the table as a compromise. While a common thought is to move into a lower-level language like assembly to improve on a program’s speed or memory use, there’s often a lot that can be done at the high level before resorting to such extremes. This, of course, is true of the Arduino platform as well, as [NerdRalph] demonstrates by shrinking the size of the Arduino core itself.

[NerdRalph] had noticed that the “blink” example program actually includes over 1 kB of extraneous code, and that more complicated programs include even more cruft. To combat this issue, he created ArduinoShrink, which seeks to make included libraries more modular and self-contained. It modifies some of the default registers and counters to use less memory and improve speed, and is also designed to improve interrupt latency as well by changing when the Arduino would otherwise disable interrupts.

While there are some limits to ArduinoShrink, such as needing to know specifics about the pins at compile time, for anyone writing programs for Arduinos that are memory-intensive or need improvements in timing, this could be a powerful new tool. If you’d prefer to go in the opposite direction to avoid ever having to learn C or assembly, though, you can always stick with running Python on your embedded devices.

Playing Snake On A PCB!

April 3, 2021 by Jenny List 11 Comments

When conversation turns to the older Nokia mobile phones, it’s unlikely to be the long battery life or ability to conjure a signal out of thin air that tickles people’s memory, instead it’s the Snake game built into the stock firmware. Snake was an addictive yet extremely simple game in which a line of pixels — the snake in question — was navigated around the screen to eat the fruit without crashing into walls or itself. As the game progressed the snake grew in length, making it a surprisingly difficult challenge. If you hanker for Snake, as [VK5HSE ] writes, you can now play it in a PCB layout.

The software in question is PCB-RND, a cross-platform open-source PCB CAD tool, and the game is achieved through the magic of user scripting. Simply download the script, run it in your favourite circuit board, and away you go!

We can’t imagine a productive use for this piece of software, but it wouldn’t surprise us to see a snake slithering into a few boards we feature. It does provide a handy reminder though of the power in your PCB CAD tool’s scripting features, something it’s likely not many of us use to their full potential.

We’ve featured [VK5HSE]’s work with PCB-RND before, in a very useful Eagle import tool.

FreeCAD Takes Off With A Rocket Design Workbench

April 2, 2021 by Donald Papp 25 Comments

Here’s how FreeCAD works: the program’s design space is separated into different “workbenches”, each of which is intended for a particular set of operations, and a piece of work can be moved between them as needed. There is a sketching workbench, a part design workbench, and now a Rocket workbench has been added to the healthy ecosystem of FreeCAD add-ons. There’s even a series of video tutorials; ain’t open source grand?

It all started when [concretedog] posted on the FreeCAD forums, making a strong case for a Rocket-themed workbench. People got interested, and a short while later [DavesRocketShop] had some useful tools up and running. Here’s a blog post by [concretedog] which goes into detail and background, and while the Rocket workbench is available via FreeCAD’s add-on manager, the very latest experimental builds are available for manual installation on [Dave]’s GitHub repository.

This sort of development and utility is exactly the kind of thing our own Elliot Williams was describing when he made the point that one of open source’s greatest strengths is in the little things, like the FreeCAD ecosystem letting people scratch strange and specific itches, and the ability to share those solutions with others.

Web Tool Cranks Up The Power On DJI’s FPV Drone

March 31, 2021 by Tom Nardi 22 Comments

Apparently, if the GPS on your shiny new DJI FPV Drone detects that it’s not in the United States, it will turn down its transmitter power so as not to run afoul of the more restrictive radio limits elsewhere around the globe. So while all the countries that have put boots on the Moon get to enjoy the full 1,412 mW of power the hardware is capable of, the drone’s software limits everyone else to a paltry 25 mW. As you can imagine, that leads to a considerable performance penalty in terms of range.

But not anymore. A web-based tool called B3YOND promises to reinstate the full power of your DJI FPV Drone no matter where you live by tricking it into believing it’s in the USA. Developed by the team at [D3VL], the unlocking tool uses the new Web Serial API to send the appropriate “FCC Mode” command to the drone’s FPV goggles over USB. Everything is automated, so this hack is available to anyone who’s running a recent version of Chrome or Edge and can click a button a few times.

There’s no source code available yet, though the page does mention they will be putting up a GitHub repository soon. In the meantime, [D3VL] have documented the command packet that needs to be sent to the drone over its MODBUS-like serial protocol for others who might want to roll their own solution. There’s currently an offline Windows-only tool up for download as well, and it sounds like stand-alone versions for Mac and Android are also in the works.

It should probably go without saying that if you need to use this tool, you’ll potentially be violating some laws. In many European countries, 25 mW is the maximum unlicensed transmitter power allowed for UAVs, so that’s certainly something to keep in mind before you flip the switch. Hackaday isn’t in the business of dispensing legal advice, but that said, we wouldn’t want to be caught transmitting at nearly 60 times the legal limit.

Even if you’re not interested in fiddling with drone radios, it’s interesting to see another practical application of the Web Serial API. From impromptu oscilloscopes to communicating with development boards and conference badges, clever developers are already finding ways to make hardware hacking easier with this new capability.

[Thanks to Jules for the tip.]

Code Talkers: Programming With Voice

March 28, 2021 by Al Williams 18 Comments

IEEE Spectrum had an interesting post covering several companies trying to sell voice programming interfaces. Not programming APIs for speech recognition, but the replacement of the traditional text editor to produce programs.

The companies, Serenade and Talon, have very different styles. Serenade has fairly normal-sounding language, whereas Talon has you use very specific phrases and can even use eye tracking to figure out what you are looking at when you issue a command. There’s also mention of two open-source products (Aenae and Caster) that require you to use a third-party speech engine.

For an example of Talon’s input, imagine you want this line of code in your program:

name=extract_word(m)

You’d say this out loud: “Phrase name op equals snake extract word paren mad.” Not exactly how Star Trek envisioned voice programming.

For accessibility, this might be workable. It is hard for us to imagine a room full of developers all talking to make their computers enter C or Python code. Until we can say, “Computer, build a graphic using the data in file hackaday-27,” we think this is not going to go mainstream.

The actual speech recognition part is pretty much a commodity now. Making a reasonable set of guesses about what people will say and what they mean by it is something else. It seems like this works best when you have a very specific and limited vocabulary, like operating a 3D printer.

Undocumented X86 Instructions Allow Microcode Access

March 26, 2021 by Al Williams 19 Comments

For an old CPU, finding all the valid instructions wasn’t very hard. You simply tried them all. Sure, really old CPUs might make it hard to tell what the instruction did, but once CPUs got illegal instruction traps, you could quickly just scan possible op codes and see what didn’t throw an exception. Modern processors, though, are quite another thing. For example, you might run a random instruction that locks up the machine or miss an instruction that would have been valid but the CPU is in the wrong mode. [Can Bölük] has a novel solution: By speculatively executing the target instruction and then monitoring the microcode sequencer, he can determine if the CPU is decoding an instruction even if it refuses to execute it.

Some unknown instructions may have power for good or evil, such as the recently announced undocumented instructions that can apparently rewrite the microcode. We expect to see a post soon on how to reprogram your Intel processor to run as a 6502 natively.

Continue reading “Undocumented X86 Instructions Allow Microcode Access” →

Machine Learning Current Sensor Snoops On MCUs

March 23, 2021 by Tom Nardi 8 Comments

Anyone who’s ever tried their hand at reverse engineering a piece of hardware has wished there was some kind of magic wand you could tap on a PCB to understand what its doing and why. We imagine that’s what put security researcher [Mark C] on the path to developing CurrentSense-TinyML, a fascinating proof of concept that uses machine learning and sensitive current measurements to try and determine what a microcontroller is up to.

The idea is simple enough: just place a INA219 current sensor between the power supply and the microcontroller under observation, and record the resulting measurements as it goes about its business. Of course in this case, [Mark] knew what the target Arduino Nano was doing because he wrote the code that blinks its onboard LED.

This allowed him to create training data for TensorFlow, which was ultimately optimized into a model that could fit onto the Arduino Nano 33 BLE Sense which stands in for our magic wand. The end result is that the model can accurately predict when the Nano has fired up its LED based on the amount of power it’s using. [Mark] has done a fantastic job of documenting the whole process, which also doubles as a great intro for putting machine learning to work on a microcontroller.

Now we already know what you’re thinking: obviously the current would go up when the LED was lit, so the machine learning aspect is completely unnecessary. That may be true in this limited context, but remember, this is just a proof of concept to base further work on. In the future, with more training data, this technique could potentially be used to identify a whole range of nuanced activities. You’d be able to see when the MCU was sitting idle, when it was writing to flash, or when it was reading from sensors. In fact, with a good enough model, it might even be possible to identify the individual sensors that are being polled.

These are early days, but we’re very interested in seeing where this research goes. It might not be magic, but if analyzing the current draw of a coffee maker can tell you how much everyone in the office is drinking, then maybe it can help us figure out what all these unlabeled ICs are doing.