A few years ago, [Kingpin] a.k.a. [Joe Grand] (A judge for the 2014 Hackaday Prize) designed the most beautiful electronic prank ever. The BSODomizer is a simple device with a pass-through connection for a VGA display and an infrared receiver. Plug the BSODomizer into an unsuspecting coworker’s monitor, press a button on a remote, and watch Microsoft’s blue screen of death appear. It’s brilliant, devious, and actually a pretty simple device if you pick the right microcontroller.
The original BSODomizer is getting a little long in the tooth. VGA is finally dead. The Propeller chip used to generate the video only generates text, and can’t reproduce Microsoft’s fancy new graphical error screens. HDMI is the future, and FPGAs have never been more accessible. For this year’s DEF CON, [Kingpin] and [Zoz] needed something to impress an audience that is just learning how to solder. They’ve revisited the BSODomizer, and have created the greatest hardware project at this year’s DEF CON.
Playing around with FPGAs used to be a daunting prospect. You had to fork out a hundred bucks or so for a development kit, sign the Devil’s bargain to get your hands on a toolchain, and only then can you start learning. In the last few years, a number of forces have converged to bring the FPGA experience within the reach of even the cheapest and most principled open-source hacker.
[Ken Boak] and [Alan Wood] put together a no-nonsense FPGA board with the goal of getting the price under $30. They basically took a Lattice iCE40HX4K, an STMF103 ARM Cortex-M3 microcontroller, some SRAM, and put it all together on a single board.
The Lattice part is a natural choice because the IceStorm project created a full open-source toolchain for it. (Watch [Clifford Wolf]’s presentation). The ARM chip is there to load the bitstream into the FPGA on boot up, and also brings USB connectivity, ADC pins, and other peripherals into the mix. There’s enough RAM on board to get a lot done, and between the ARM and FPGA, there’s more GPIO pins than we can count.
Modeling an open processor core? Sure. High-speed digital signal capture? Why not. It even connects to a Raspberry Pi, so you could use the whole affair as a high-speed peripheral. With so much flexibility, there’s very little that you couldn’t do with this thing. The trick is going to be taming the beast. And that’s where you come in.
Every year, new models of laptops arrive on the shelves. This means that old laptops usually end up in landfills, which isn’t exactly ideal. If you don’t want to waste an old or obsolete laptop, though, there’s a way to reuse at least the screen out of one. Simply grab an FPGA off the shelf and get to work.
[Martin] shows us all how to perform this feat on our own, and goes into great detail about how all of the electronics involved work. Once everything was disassembled and the FPGA was wired up, it took him a substantial amount of time just to turn the display on. From there it was all downhill: [Martin] can now get any pattern to show up on the screen, within reason. The only limit to his display now seems to be the lack of external RAM. He currently uses the setup to drive an impressive-looking clock.
This is a big step from days passed where it was next to impossible to repurpose a laptop screen. Eventually someone discovered a way to drive these displays, and now there are cheap electronics from China that can usually get a screen like this running. It’s impressive to see it done from scratch, though, and the amount of detail in the videos are a great way to understand how everything is working.
For humans, moving our arms and hands onto an object to pick it up is pretty easy; but for manipulators, it’s a different story. Once we’ve found the object we want our robot to pick up, we still need to plan a path from our robot hand to the object all the while lugging the remaining limbs along for the ride without snagging them on any incoming obstacles. The space of all possible joint configurations is called the “joint configuration space.” Planning a collision-free path through them is called path planning, and it’s a tricky one to solve quickly in the world of robotics.
These days, roboticists have nailed out a few algorithms, but executing them takes 100s of milliseconds to compute. The result? Robots spend most of their time “thinking” about moving, rather than executing the actual move.
It’s worth asking: why is this problem so hard? How did hardware make it faster? There’s a few layers here, but it’s worth investigating the big ones. Planning a path from point A to point B usually happens probabilistically (randomly iterating to the finishing point), and if there exists a path, the algorithm will find it. The issue, however, arises when we need to lug our remaining limbs through the space to reach that object. This feature is called the swept volume, and it’s the entire shape that our ‘bot limbs envelope while getting from A to B. This is not just a collision-free path for the hand, but for the entire set of joints.
Encoding a map on a computer is done by discretizing the space into a sufficient resolution of 3D voxels. If a voxel is occupied by an obstacle, it gets one state. If it’s not occupied, it gets another. To compute whether or not a path is OK, a set of voxels that represent the swept volume needs to be compared against the voxels that represent the environment. Here’s where the FPGA kicks in with the speed bump. With the hardware implementation, voxel occupation is encoded in bits, and the entire volume calculation is done in parallel. Nifty to have custom hardware for this, right?
We applaud the folks at Duke University for getting this up-and-running, and we can’t wait to see custom “robot path-planning chips” hit the market some day. For now, though, if you’d like to sink your teeth into seeing how FPGAs can parallelize conventional algorithms, check out our linear-time sorting feature from a few months back.
Any maker worth their bits will look for new ways to challenge themselves. [Robert Fotino], a computer science student at the University of California, is doing just that: designing and building his own lightweight hobbyist game console that he has appropriately named Consolite.
[Fotino] wrote his own compiler in C++ that converts from C-like languages to a custom-designed assembler that he has dubbed Consolite Assembly. To test his code, he also wrote an emulator before loading it onto the Mimas V2 FPGA board. Presently, Consolite uses 64KiB of main memory and 48 KiB of video memory; a future version will have 32 bit support to make better use of the Mimas’ 64 MiB of on board ram, but the current 16-bit version is a functional proof of concept.
An SD card functions as persistent storage for up to 256 programs, which can be accessed using the hardware switches on the Mimas, with plans to add user access in the form of saving game progress, storage outside of main memory, etc. — also in a future update that will include audio support.
As it stands, [Fotino] has written his own versions of Breakout, Tetris, and Tron to show off his project.
Not wanting for diligence, [Fotino] has provided thorough documentation of nearly every step along the way in his blog posts and on GitHub if you are looking for guidelines for any similar projects you might have on the back burner — like an even tinier game console.
One day [Andy] was cruising around eBay and spotted something interesting. Forty Virtex-E FPGAs for two quid each. These are the big boys of the FPGA world, with 512 user IO pins, almost 200,000 logic gates, packed into a 676-ball BGA package. These are not chips designed for the hobbyist. These chips are not designed for boards with less than six layers. These chips aren’t even designed for boards with 6/6mil tolerances from the usual suspects in China. By any account, a 676-ball package is not like a big keep out sign for hobbyists. You don’t turn down a £2 class in advanced PCB design, though, leading to one of the most impressive ‘I just bought some crap on eBay’ projects we’ve seen.
The project [Andy] had in mind for these chips was a generic dev board, which meant breaking out the IO pins and connecting some SRAM, SDRAM, and Flash memory. The first issue with this project is escape routing all the balls. Xilinx published a handy application note that recommends specific design parameters for the traces of copper under the chip. Unfortunately, this was a six-layer board, and the design rules in the application note were for 5/5mil traces. [Andy]’s board house can’t do six-layer boards, and their design rules are for 6/6mil traces. To solve this problem, [Andy] just didn’t route the inner balls, and hoped the 5mil traces would work out.
With 676 tiny little pads on a PCB, the clocks routed, power supply implemented, too many decoupling caps on the back, differential pairs, static RAM, a few LEDs placed just for fun, [Andy] had to solder this thing up. Since the FPGA was oddly one of the less expensive items on the BOM, he soldered that first, just to see if it would work. It did, which meant it was time to place the RAM, Flash, and dozens of decoupling caps. Everything went relatively smoothly – the only problem was the tiny 0402 decoupling caps on the back of the board. This was, by far, the hardest part of the board to solder. [Andy] only managed to get most of the decoupling caps on with a hot air gun. That was good enough to bring the board up, but he’ll have to figure some other way of soldering those caps for the other 30 or so boards.
Slowly, very slowly, the time when we don’t subject embedded beginners to AVRs and PICs is coming. At a glacial pace, FPGA development platforms are becoming ever more capable and less expensive. [Eric Brombaugh] has been playing around with both ARMs and FPGAs for a while now and decided to combine these two loves into a single board that’s capable of a lot.
This board is fittingly called an STM32F303 + ice5 development board, and does exactly what it says on the tin. There’s an STM32F303 on board providing a 32-bit CPU running at 72 MHz, 48 kB of SRAM, a quarter meg of Flash, and enough peripherals to keep anyone happy. The FPGA side of this board is a Lattice iCE5 with about 3k Look Up Tables (LUTs), and one time programmable non-volatile config memory.
The connections between the ARM and FPGA include a dedicated SPI port, and enough GPIOs to implement full-duplex I2S and a USART. Like all good projects, [Eric] has shared all the files, schematics, and BOMs required to make this board your very own reality, and has provided a few links to the development toolchains. While the FPGA is from Lattice’s ice40 family, it’s not supported by the Open Source Project Icestorm toolchain. Still, it’s a very capable board for ARM and FPGA development.