a 3d mesh of a rabbit, and a knit version of the same

Knitting Software Automatically Converts 3D Models Into Machine-knit Stuffies

June 14, 2019 by 20 Comments

We’ve seen our fair share of interesting knitting hacks here at Hackaday. There has been a lot of creative space explored while mashing computers into knitting machines and vice versa, but for the most part the resulting knit goods all tend to be a bit… two-dimensional. The mechanical reality of knitting and hobbyist-level knitting machines just tends to lend itself to working with a simple grid of pixels in a flat plane.

However, a team at the [Carnegie Mellon Textiles Lab] have been taking the world of computer-controlled knitting from two dimensions to three, with software that can create knitting patterns for most any 3D model you feed it. Think of it like your standard 3D printing slicer software, except instead of simple layers of thermoplastics it generates complex multi-dimensional chains of knits and purls with yarn and 100% stuffing infill.

The details are discussed and very well illustrated in their paper entitled Automatic Machine Knitting of 3D Meshes and a video (unfortunately not embeddable) shows the software interface in action, along with some of the stuffing process and the final adorable (ok they’re a little creepy too) stuffed shapes.

Since the publication of their paper, [the Textiles Lab] has also released an open-source version of their autoknit software on GitHub. Although the compilation and installation steps look non-trivial, the actual interface seems approachable by a dedicated hobbyist. Anyone comfortable with 3D slicer software should be able to load a model, define the two seams necessary to close the shape, which will need to be manually sewn after stuffing, and output the knitting machine code.

Previous knits: the Knit Universe, Bike-driven Scarf Knitter, Knitted Circuit Board.

This Week In Security: Use Emacs, Crash A Windows Server, And A Cryptocurrency Heist

June 14, 2019 by 5 Comments

It looks like Al was right, we should all be using Emacs. On the 4th of June, [Armin Razmjou] announced a flaw in Vim that allowed a malicious text file to trigger arbitrary code execution. It’s not every day we come across a malicious text file, and the proof of concept makes use of a clever technique — escape sequences hide the actual payload. Printing the file with cat returns “Nothing here.” Cat has a “-v” flag, and that flag spills the secrets of our malicious text file. For simplicity, we’ll look at the PoC that doesn’t include the control characters. The vulnerability is Vim’s modeline function. This is the ability to include editor options in a text file. If a text file only works with 80 character columns, a modeline might set “textwidth=80”. Modeline already makes use of a sandbox to prevent the most obvious exploits, but [Armin] realized that the “:source!” command could run the contents of a file outside that sandbox. “:source! %” runs the contents of the current file — the malicious text file.

:!uname -a||" vi:fen:fdm=expr:fde=assert_fails("source\!\ \%"):fdl=0:fdt="

Taking this apart one element at a time, the “:!” is the normal mode command to run something in the shell, so the rest of the line is what gets run. “uname -a” is the arbitrary command, benign in this case. Up next is the OR operator, “||” which fully evaluates the first term first, and only evaluates what comes after the operator if the first term returns false. In this case, it’s a simple way to get the payload to run even though the rest of the line is garbage, as far as bash is concerned. “vi:” informs Vim that we have a modeline string. “:fen” enables folding, and “:fdm=expr” sets the folding method to use an expression. This feature is usually used to automatically hide lines matching a regular expression. “:fde=” is the command to set the folding expression. Here’s the exploit, the folding expression can be a function like “execute()” or “assert_fails()”, which allows calling the :source! command. This pops execution out of the sandbox, and begins executing the text file inside vim, just as if a user were typing it in from the keyboard. Continue reading “This Week In Security: Use Emacs, Crash A Windows Server, And A Cryptocurrency Heist” →

Augmented Arthropod Gets A Self-Balancing Ride

June 14, 2019 by 3 Comments

There are many people who find being around insects uncomfortable. This is understandable, and only likely to get worse as technology gives these multi-legged critters augmented bodies to roam around with. [tech_support], for one, welcomes our new arthropod overlords, and has even built them a sweet new ride to get around in.

The build follows the usual hallmarks of a self-balancing bot, with a couple of interesting twists. There’s twin brushed motors for drive, an an Arduino Uno running the show. Instead of the more usual pedestrian IMUs however, this rig employs the Bosch BNO055 Absolute Orientation Sensor. This combines a magnetometer, gyroscope, and accelerometer all on a single die, and handles all the complicated sensor fusion maths onboard. This allows it to output simpler and more readily usable orientation data.

The real party piece is even more interesting, however. Rather than radio control or a line following algorithm, this self-balancer instead gets its very own insect pilot. The insect is placed in a small chamber with ultrasonic sensors used to determine its position. The insect may then control the movement of the bot by moving around this chamber itself. The team have even developed a variety of codes to dial in the sensor system for different types of insect.

It’s not the first time we’ve seen insects augmented with robotic hardware, and we doubt it will be the last. If you’re working on a mad science project of your own, drop us a line. Video after the break.

Continue reading “Augmented Arthropod Gets A Self-Balancing Ride” →

Hyperlinking Comes To GitHub Via Extension

June 14, 2019 by 8 Comments

If you are browsing GitHub it is very tempting to open up the source code to some project and peek at how it works. The code view is easy to read, but the viewer lacks one important feature: the ability to click on an included file and find it. The Octolinker extension fixes that oversight.

If you want to try it without installing the extension, there is a mock-up demo available. Even though the demo wants you to click on specific things, if you don’t play by the rules it will still do the right thing and take you to either the code on GitHub or an appropriate page. You can even substitute the demo URL for github.com and try it out on any GitHub page without the extension.

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Divide To Conquer Capacitive Touch Problems

June 13, 2019 by 8 Comments

Back in the day, all of your music was on a shelf (or in milk crates) and the act of choosing what to listen to was a tangible one. [Michael Teeuw] appreciates the power of having music on demand, but misses that physical aspect when it comes time to “put something on”. His solution is a hardware controller that he calls MusicCubes.

Music cube makes selection using RFID, and touching to the right raises the volume level

This is a multi-part project, but the most recent rework is what catches our eye. The system uses cubes with RFID tags in them for each album. This part of the controller works like a charm, just set the cube in a recessed part of the controller — like Superman’s crystals in his fortress of solitude — and the system knows you’ve made your decision. But the touch controls for volume didn’t work as well. Occasionally they would read a false touch, which ends up muting the system after an hour or so. His investigations led to the discovery that the capacitive touch plates themselves needed to be smaller.

Before resorting to a hardware fix, [Michael] tried to filter out the false positives in software. This was only somewhat successful so his next attempt was to cut the large touch pads into four plates, and only react when two plates register a press at one time.

He’s using an MPR121 capacitive touch sensor which has inputs for up to 12-keys so it was no problem to make this change work with the existing hardware. Surprisingly, once he had four pads for each sensor the false-positives completely stopped. The system is now rock-solid without the need to filter for two of this sub-pads being activated at once. Has anyone else experienced problems with large plates as the touch sensors? Can this be filtered easily or is [Michael’s] solution the common way to proceed? Share your own capacitive touch sensor tips in the comments below!

Want to get a look at the entire project? Start with step one, which includes a table of contents for the other build logs.

A Tetris Clock

June 13, 2019 by 6 Comments

We have had no shortage of clock projects over the years, and this one is entertaining because it spells the time out using Tetris-style blocks. The project looks good and is adaptable to different displays. The code is on GitHub and it relies on a Tetris library that has been updated to handle different displays and even ASCII text.

[Brian] wanted to use an ESP8266 development board for the clock, but the library has a bug that prevents it from working, so he used an ESP32 board instead. The board, a TinyPICO, has a breakout board that works well with the display.

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Let The Cards Fall Where They May, With A Robotic Rain Man

June 13, 2019 by 15 Comments

Finally,  a useful application for machine vision! Forget all that self-driving nonsense and facial recognition stuff – we’ve finally got an AI that can count cards at the blackjack table.

The system that [Edje Electronics] has built, dubbed “Rain Man 2.0” in homage to the classic title character created by [Dustin Hoffman] for the 1988 film, aims to tilt the odds at the blackjack table away from the house by counting cards. He explains one such strategy, a hi-low count, in the video below, which Rain Man 2.0 implements with the help of a webcam and YOLO for real-time object detection. Cards are detected in any orientation based on their suit and rank thanks to an extensive training set of card images, which [Edje] generated synthetically via some trickery with OpenCV. A script automated the process and yielded a rich training set of 50,000 images for YOLO. A Python program implements the trained model into a real-time card counting application.

Rain Man 2.0 is an improvement over [Edje]’s earlier Tensor Flow card counter, but it still has limitations. It can’t count into a six-deck shoe as the fictional [Rain Man] could, at least not yet. And even though cheater’s justice probably isn’t all cattle prods and hammers these days, the hardware needed for this hack is not likely to slip past casino security. So [Edje] has wisely limited its use to practicing his card counting skills. Eventually, he wants to turn Rain Man into a complete AI blackjack player, and explore its potential for other games and to help the visually impaired.

Continue reading “Let The Cards Fall Where They May, With A Robotic Rain Man” →