Ikea Furniture Hacks Make Accessibility More Accessible

The ThisAbles project is a series of 3D-printed IKEA furniture hacks making life easier for those without full use of their bodies. Since IKEA furniture is affordable and available across most of the planet, it’s the ideal target for a project that aims to make 3D-printed improvements accessible to everyone.

These hacks fit all meanings of the word “accessible”: Available worldwide, affordable, and helping people overcome physical barriers of everyday living. ThisAbles has support of multiple organizations including IKEA Israel. In their short introductory video (embedded below the break) they explained their process to find ways to make big impacts with simple 3D-printed modifications. From bumpers protecting furniture against wheelchair damage, to handles that allow drawers to be opened without fine fingertip control. Each of these designs also fit the well-known IKEA aesthetic, including their IKEA style illustrated manuals.

The site launched with thirteen downloadable solutions, but they have ambitions for more with user feedback. There’s a form where people can submit problems they would like to see solved, or alternatively, people can submit solutions they’ve already created and wish to share with the world. Making small changes to commodity IKEA furniture, these 3D printed accessories will have far more impact on people’s lives than the average figurine trinket on Thingiverse. It’s just the latest way we can apply hacker ingenuity to help others to do everything from simple daily tasks to video gaming.

[via Washington Post]

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Printed Perching Pals Proliferate

Anansi in African folktale is a trickster and god of stories, usually taking physical form of a spider. Anansi’s adventures through oral tradition have adapted to the situation of people telling those stories, everything ranging from unseasonable weather to living a life in slavery. How might Anansi adapt to the twenty-first century? [odd_jayy] imagined the form of a cyborg spider, and created Asi the robot companion to perch on his shoulder. Anyone who desire their own are invited to visit Asi’s project page.

Asi was inspired by [Alex Glow]’s Archimedes, who also has a project page for anyone to build their own. According to [Alex] at Superconference 2018, she knew of several who have done so, some with their own individual customization. [odd_jayy] loved the idea of a robot companion perched on his shoulder but decided to draw from a different pool of cultural folklore for Asi. Accompanying him to various events like Sparklecon 2019, Asi is always a crowd pleaser wherever they go.

Like every project ever undertaken, there is no shortage of ideas for Asi’s future and [odd_jayy] listed some of them in an interview with [Alex]. (Video after the break.) Adding sound localization components will let Asi face whoever’s speaking nearby. Mechanical articulation for legs would allow more dynamic behaviors while perched, but if the motors are powerful enough, Asi can walk on a surface when not perched. It’s always great to see open source projects inspire even more projects, and watch them as they all evolve in skill and capability. If they all become independently mobile, we’ll need clarification when discussing the average velocity of an unladen folklore robot companion: African or European folklore?

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New Part Day: Pyboard D is Smaller, Wireless, and Has Expansion Modules

Historically, microcontrollers’ limited computing power and storage space meant software had to be written in low-level languages out of necessity. In recent years small affordable chips grew powerful enough that they could theoretically run higher level languages, sparking numerous efforts to turn that theory into reality. MicroPython delivered on this promise in a big way when their Kickstarter-funded pyboard was delivered along with its open source software. Several years have since passed, and now it is time for an upgraded pyboard: the D-series.

We’ve talked with [Damien George] back when the original Kickstarter was still underway. Since the launch of pyboard and release of MicroPython source code, we’ve played with ports running on an ESP8266 and on a BBC micro:bit. The software ecosystem has continued to grow, most recently we looked at LittlevGL graphics library. But just because all the flashy action has been happening on the software side doesn’t mean the hardware side has been sitting stagnant.

Pyboard-D upgraded from original pyboard’s STM32F4 to more capable STM32F7 chips. Witnessing the popularity of MicroPython on networked darlings ESP8266 and ESP32, there will be a pyboard D variant with a Murata 1DX on board for WiFi and Bluetooth connectivity. The new pyboard will be extremely compact with limited edge connections so a fine-pitched connector is required to bring out all the pins. To bring the new pyboard back to its educational and tinkerer roots, a breakout board will take those pins and spread them out in a breadboard friendly form factor. These breakout boards can also host small (12 mm x 12 mm) “tiles” to add individual features.

The wireless pyboard D will obviously invite comparison tests with an ESP32 running MicroPython, and its hardware expansion tiles invites comparison with Adafruit’s Wings. It’ll be interesting to see how they fare once widely available and we can get our hands on them. If you’ve picked up an earlier release at FOSDEM 2019, we invite you to share your experience in comments.

[via Adafruit blog]

Octavo Systems Shows Off With Deadbug Linux Computer

Once upon a time, small Linux-capable single board computers were novelties, but not anymore. Today we have a wide selection of them, many built around modules we could buy for our own projects. Some of the chipset suppliers behind these boards compete on cost, others find a niche to differentiate their product. Octavo Systems is one of the latter offering system-in-package (SiP) modules that are specifically designed for easy integration. They described how simple it would be to build a minimal computer using their SC335x C-SiP, and to drive the point home they brought a deadbug implementation to Embedded World 2019. [Short video after the break.]

Most of us encounter Octavo modules as the heart of a BeagleBoard. Their increasing integration made tiny wonders like PocketBeagle possible. But bringing out all those pins for use still required a four-layer circuit board. Octavo’s pitch for hardware professionals center around how easy integration saves time for faster time to market, and fortunately for us easy integration also translates to a more accessible device for our projects. It’s one thing to publish a document describing a hypothetical single-layer PCB for an Octavo module, it’s quite something else to show that concept in action with no PCB at all.

Of course, this little machine only has access to a fraction of the module’s functionality, and it is certainly overkill if the objective is just to blink a few LEDs. If so, we’d just use 555 timers! But it does show how simple a bare bones “Hello World” machine can be built, removing intimidation factor and invite more people to come play.

One of the three top winners in our circuit sculpture contest was a wireframe Z80 computer. There’s quite a jump from a Z80 to an Octavo SC335x, but we’ve already seen one effort by [Zach] over Supercon 2018 weekend to build a deadbug computer with an Octavo module. It won’t be long before someone one-ups this minimalist LED blinker with something more sophisticated and we can’t wait to see it. Continue reading “Octavo Systems Shows Off With Deadbug Linux Computer”

Uncertain Future of Orphaned Jibo Robots Presents Opportunities

In our modern connected age, our devices have become far more powerful and useful when they could draw upon resources of a global data network. The downside of a cloud-connected device is the risk of being over-reliant on computers outside of our own control. The people who brought a Jibo into their home got a stark reminder of this fact when some (but not all) Jibo robots gave their owners a farewell message as their servers are shut down, leaving behind little more than a piece of desktop sculpture.

Jibo launched their Indiegogo crowdfunding campaign with the tagline “The World’s First Social Robot For The Home.” Full of promises of how Jibo will be an intelligent addition to a high tech household, it has always struggled to justify its price tag. It cost as much as a high end robot vacuum, but without the house cleaning utility. Many demonstrations of a Jibo’s capabilities centered around its voice control, which an Amazon Echo or Google Home could match at a fraction of the price.

By the end of 2018, all assets and intellectual property have been sold to SQN Venture Partners. They have said little about what they planned to do with their acquisition. Some Jibo owner still hold hope that there’s still a bright future ahead. Both on the official forums (for however long that will stay running) and on unofficial channels like Reddit. Other owners have given up and unplugged their participation in this social home robotics experiment.

If you see one of these orphans in your local thrift store for a few bucks, consider adopting it. You could join the group hoping for something interesting down the line, but you’re probably more interested in its hacking potential: there is a Nvidia Jetson inside good for running neural networks. Probably a Tegra K1 variant, because Jibo used the Jetson TK1 to develop the robot before launch. Jibo has always promised a developer SDK for the rest of us to extend Jibo’s capabilities, but it never really materialized. The inactive Github repo mainly consists of code talking to servers that are now offline, not much dealing directly with the hardware.

Jibo claimed thousands were sold and, if they start becoming widely available inexpensively, we look forward to a community working to give new purpose to these poor abandoned robots. If you know of anyone who has done a teardown to see exactly what’s inside, or if someone has examined upgrade files to create custom Jibo firmware, feel free to put a link in the comments and help keep these robots out of e-waste.

If you want to experiment with power efficient neural network accelerators but rather work with an officially supported development platform, we’ve looked at the Jetson TK1 successors TX1 and TX2. And more recently, Google has launched one of their own, as has our friends at Beaglebone.

Leigh Johnson’s Guide To Machine Vision On Raspberry Pi

We salute hackers who make technology useful for people in emerging markets. Leigh Johnson joined that select group when she accepted the challenge to build portable machine vision units that work offline and can be deployed for under $100 each. For hardware, a Raspberry Pi with camera plus screen can fit under that cost ceiling, and the software to give it sight is the focus of her 2018 Hackaday Superconference presentation. (Video also embedded below.)

The talk is a very concise 13 minutes, so Leigh flies through definitions of basic terms, before quickly naming TensorFlow and Keras as the tools she used. The time she saved here was spent on explaining what convolutional neural networks are and how they work, just enough to prepare the audience. But all of that is really just background, the meat of the talk is self-contained examples that Leigh has put together and made available online. I love to see that since it means you go beyond just watching and try it out for yourself. Continue reading “Leigh Johnson’s Guide To Machine Vision On Raspberry Pi”

New Kinect Sensor Switch Focus From Gamers To Developers

Microsoft’s Kinect may not have found success as a gaming peripheral, but recognizing that a depth sensor is too cool to leave for dead, development continued even after Xbox gaming peripherals were discontinued. This week their latest iteration emerged and we can get it in the form of Azure Kinect DK. This is a developer’s kit focused on exploring new applications for this technology, not a gaming peripheral we had to hack before we could use in our own projects.

Packaged into a peripheral that plugs into a PC via USB-C, it is more than the core depth sensor module announced last year but less than a full consumer product. Browsing its 10-page specification (PDF) with comparisons to second generation Kinect sensor bar, we see how this technology has evolved. Physical size and weight has dropped, as has power consumption. Auxiliary capabilities has improved with an expanded microphone array, IMU with gyro in addition to accelerometer, and the RGB camera has been upgraded to 4K resolution.

But the star of the show is a new continuous-wave time-of-flight depth sensor, presented at the 2018 IEEE ISSCC conference. (Full text requires IEEE membership, but a digest form is available via ResearchGate.) Among its many advancements, we expect the biggest impact to be its field of view. Default of 75 x 65 degrees is already better than its predecessors (64 x 45 for first generation Kinect, 70 x 60 for second) but there is an option to trade resolution for coverage by switching to a wide-angle mode of 120 x 120 degrees. Significantly wider than other depth cameras like Intel’s RealSense D400 series or Occipital’s Structure.

Another interesting feature is built-in synchronization. Many projects using multiple Kinect sensors ran into problems because they interfered with each other. People hacked around the problem, of course, but now they don’t have to: commodity 3.5 mm jacks allow multiple Azure Kinect DK to be daisy chained together so they play nicely and take turns.

From its name we were worried this product would require Microsoft’s Azure cloud service in some way and be crippled without it. Based on information released so far, it appears developers have access to all the same data streams as previous sensors. Azure tie-in takes the form of optional SDKs that make it easier to do things like upload data for processing in Azure cloud-based recognition services.

And finally, Azure Kinect DK’s price tag of $399 is significantly higher than a Kinect game peripheral, but it is a low volume product for developers. Perhaps high volume consumer products built on this technology will cost less, but that remains to be seen. In the meantime, you have alternative tools for solving similar problems. For example if you are building your own AR headset, you might use Intel’s latest RealSense camera for vision based inside-out motion tacking.