Minimalist Robot Arm Really Stacks Up

August 19, 2021 by Dan Maloney 7 Comments

There’s nothing like a little weekend project, especially one that ends up better than you expected. And when you literally build a robotic arm out of workshop scraps, so much the better.

Longtime readers will no doubt recognize the build style used here as that of [Norbert Heinz], aka “Homofaciens” on YouTube. [Norbert] has a way of making trash do his bidding, and has shown us all kinds of seemingly impossible feats of mechatronics with just what’s lying around. In this case, his robot arm is made from scrap wooden roofing battens, or what we’d call furring strips here in the US. The softwood isn’t something you’d think would make a great material for building robots, but [Norbert] makes its characteristics work for him, like using wax-lubricated holes for hinge points. Steppers and lead screws cannibalized from an old CNC build, along with the drive electronics, provide the motion. It’s a bit — compliant — but precise enough to pick up nuts and stack them nicely. The video below gives an overview of the build, and detailed instructions are available too.

We always appreciated [Norbert]’s minimalist builds, and seeing what can be accomplished with almost nothing is always inspirational. If you’re not familiar with his work, check out his cardboard and paperclip CNC plotter, his tin can encoders, or his plasma-powered printer.

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Arm Researchers Announce The PlasticArm

July 23, 2021 by Chris Lott 19 Comments

If the Cortex family of embedded microprocessors aren’t flexible enough for your designs, an article published this week (click here for the PDF version) in the journal Nature might be of interest. We’re not talking flexibility in terms of features, but real, physical flexibility of the microprocessor itself. A research team from Arm Ltd. has developed the PlasticArm, which is a 32-bit processor derived from the Cortex-M0+ family.

They accomplished this by constructing a CPU from metal-oxide thin-film transistors (TFT) on a polyimide substrate, the resultant chip being called a natively flexible microprocessor. While much of the hype focuses on the flexibility aspect, we think the real innovation here is the low cost. The processes used to deposit transistors onto silicon wafers is much more expensive than those on this flexible substrate.

Don’t get too excited just yet, because there were some compromises made along the way. Modern microprocessor silicon dies are measured in the tens of microns, but the PlasticArm total die size is a comparatively whopping 9 mm square. The researchers were appropriately focused on the core CPU, and the auxiliary building blocks such as ROM and RAM seem almost an afterthought. With only 456 bytes of program store and 128 bytes of RAM, only the tiniest of applications are suited to this chip. Other compromises were made, such as no internal registers — they are mapped to the external RAM — and the CPU runs a lot slower than we’re used to, topping out at 29 kHz (note: k not M).

There are certainly some challenges with this new technology, and we won’t be designing with these chips any time soon. But it has the potential to offer benefits in certain niche applications where low-cost and/or flexibility is more important than processor speed and performance.

Is 32-bits Really Dead?

June 6, 2021 by Chris Lott 101 Comments

While some of us are still clinging onto our favorite 8-bit microprocessors, ARM announced they will be killing off the 32-bit architecture in 2022 and/or 2023. Over on the GaryExplains YouTube channel, [Gary Sims] posted a great review of the current 32- vs 64-bit state-of-affairs — not just for ARM but for Intel and AMD processors as well. And it’s a dismal outlook for you 32-bit fans.

ARM announced last Fall that there would be no more 32-bit support as of 2022, then this March they made a similar announcement but with a 2023 deadline. [Gary] tries to parse these statements, and takes an educated guess at what the disparity means (spoiler alert — he predicts that one more 32-bit core will soon be released).

[Gary] clearly breaks down the 32-bit situation by operating systems such as Linux, Windows, MacOS, Android, and iOS, and how all of these have been transitioning to 64-bits over recent years. He does a thorough job, and concludes that the transition is already well underway. And while Linux and Windows have not completely dropped 32-bit support, the writing is on the wall.

Take note, however, that this discussion regards the Cortex-A family of cores found in smart phones, tablets, computers, and powerful embedded applications like autonomous vehicles. The popular 32-bit Cortex-M family of low-cost / low-power cores that are used in so many embedded system designs will remain 32-bits for the foreseeable future.

After watching [Gary]’s presentation, if you want to learn more, check out the writeup that [Maya Posch] did on the details of the latest ARMv9 ISA a few weeks ago. Also watch this 8-bit vs 32-bit presentation by our Editor-in-Chief [Mike Szczys]. Despite being from five years ago, it is still quite applicable today. What about 16-bit MCUs — the old Intel/AMD embedded 80186 processor, the 8051 follow-ons like the 80C196, 80C251, or 8051XA, the 6502 follow-ons like the 65C816, Zilog’s Z8000, the Renesas M16C, etc. — is anyone using them anymore? If so, or if you’re using a 4-bit MCU these days, let us know in the comments below.

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Deep Learning Enables Intuitive Prosthetic Control

May 27, 2021 by Lewin Day 7 Comments

Prosthetic limbs have been slow to evolve from simple motionless replicas of human body parts to moving, active devices. A major part of this is that controlling the many joints of a prosthetic is no easy task. However, researchers have worked to simplify this task, by capturing nerve signals and allowing deep learning routines to figure the rest out.

The prosthetic arm under test actually carries a NVIDIA Jetson Nano onboard to run the AI nerve signal decoder algorithm.

Reported in a pre-published paper, researchers used implanted electrodes to capture signals from the median and ulnar nerves in the forearm of Shawn Findley, who had lost a hand to a machine shop accident 17 years prior. An AI decoder was then trained to decipher signals from the electrodes using an NVIDIA Titan X GPU.

With this done, the decoder model could then be run on a significantly more lightweight system consisting of an NVIDIA Jetson Nano, which is small enough to mount on a prosthetic itself. This allowed Findley to control a prosthetic hand by thought, without needing to be attached to any external equipment. The system also allowed for intuitive control of Far Cry 5, which sounds like a fun time as well.

The research is exciting, and yet another step towards full-function prosthetics becoming a reality. The key to the technology is that models can be trained on powerful hardware, but run on much lower-end single-board computers, avoiding the need for prosthetic users to carry around bulky hardware to make the nerve interface work. If it can be combined with a non-invasive nerve interface, expect this technology to explode in use around the world.

[Thanks to Brian Caulfield for the tip!]

Raspberry Pi RP2040: Hands-On Experiences From An STM32 Perspective

May 19, 2021 by Maya Posch 97 Comments

The release of the Raspberry Pi Foundation’s Raspberry Pi Pico board with RP2040 microcontroller has made big waves these past months in the maker community. Many have demonstrated how especially the two Programmable I/O (PIO) state machine peripherals can be used to create DVI video generators and other digital peripherals.

Alongside this excitement, it raises the question of whether any of this will cause any major upheaval for those of us using STM32, SAM and other Cortex-M based MCUs. Would the RP2040 perhaps be a valid option for some of our projects? With the RP2040 being a dual Cortex-M0+ processor MCU, it seems only fair to put it toe to toe with the offerings from one of the current heavyweights in the 32-bit ARM MCU space: ST Microelectronics.

Did the Raspberry Pi Foundation pipsqueak manage to show ST’s engineers how it’s done, or should the former revisit some of their assumptions? And just how hard is it going to be to port low-level code from STM32 to RP2040? Continue reading “Raspberry Pi RP2040: Hands-On Experiences From An STM32 Perspective” →

The ARMv9 ISA, And What It Can Do For You

May 10, 2021 by Maya Posch 38 Comments

The number of distinct ARM Instruction Set Architectures (ISA) versions has slowly increased, with Arm adding a new version every few years. The oldest ISA version in common use today is ARMv6, with the ARMv6 ISA (ARM11) found in the original Raspberry Pi SBC and Raspberry Pi Zero (BCM2835). The ARMv6 ISA was introduced in 2002, followed by ARMv7 in 2005 (start of Cortex-A series) and ARMv8 in 2011. The latter was notable for adding 64-bit support.

With ARMv7 being the first of the Cortex cores, and ARMv8 adding 64-bit support in the form of AArch64, what notable features does ARMv9 bring to the table? As announced earlier this year, ARMv9’s focus appears to be on adding a whole host of features that should improve vector processing (vector extensions, or SVE) as well as digital signal processing (DSP) and security, with its Confidential Compute Architecture (CCA).

In addition to this, ARMv9 also includes all of the features that were added with ARMv8.1, v8.2, v8.3 and so on. In essence, this makes an ARMv9-based processor theoretically capable of going toe-to-toe with the best that Intel and AMD have to offer.

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Debug ARM Virtually

April 23, 2021 by Al Williams 8 Comments

With the advent of super powerful desktop computers, many developers make use of some sort of virtual or psuedo-virtual machines (VM). We run Windows in a VM and do kernel development in a VM, too. If you are emulating the same kind of computer you are on then the process is simpler, but it is possible to run, say, ARM code on an x86 (or vice versa) but with possibly slower performance than running natively. QEMU is probably the best-known program that allows a CPU to run code targeting a different CPU, but — by default — it targets desktop, laptop, and server-class machines, not tiny embedded boards. That’s where xPack QEMU Arm comes in. It allows you to run and debug embedded Cortex-M devices in an emulated environment on a host computer.

The tool supports boards like the Maple — which means it should support bluepill, along with popular boards such as the Nucleo, some discovery boards, and several from Olimex. They have plans to support several popular boards from TI, Freescale, and others, but no word on when that will happen. You can see a decidedly simple video example from [EmbeddedCraft] of blinking a virtual LED in the video below, although you might like to mute your audio before playing it.

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