After intensely studying many images of barn doors and hardware, [MotoGeeking] decided on the right wheels and went from there. Kick scooter wheels fit the bill nicely, since they are designed to support a lot of weight and come with their own bearings and spacers. And they’re cheap, too — just $9 for a pair.
[MotoGeeking] found some C channel extruded aluminium that seemed to be a perfect match for the wheels, but the wheel was quick to bind whenever it touched the sides. He solved that one by epoxying a length of round bar into the bottom corners. This allows the wheel to move freely while forcing it to stay centered in the track.
In designing the 1/4″ aluminium brackets, [MotoGeeking] took a measure thrice, order once approach to selecting the fasteners. You probably know by now that McMaster-Carr has free CAD drawings for every little thing. [MotoGeeking] imported the ones he liked into Illustrator and built around them. This helped him get it right the first time and kept the headaches and hair-tearing away. Watch the giant door skeleton glide effortlessly on its track after the break.
Usually, t-shirt designs are screen printed, but that’s so old school. You have to make the silkscreen and then rub paint all over – it’s clearly a technique meant for the past. Well, fear not, as [RCLifeOn] is here to bring us to the future with 3D Printed T-Shirt Designs.
[RCLifeOn] affixes t-shirts to his print build platform and boom: you’ve got 3D printed graphics. He started by using PLA which, while it looked great, wasn’t up to a tussle with a washing machine. However, he quickly moved on to NinjaFlex which fended much better in a wash cycle. While the NinjaFlex washed better, [RCLifeOn] did have some issues getting the NinjaFlex to adhere to the t-shirt. With a little persistence and some settings tweaking, he was able to come out ahead with a durable and aesthetically pleasing result.
Now, 3D printing isn’t going to replace screen printing, but it’s also not going to replace injection molding. What 3D printing lacks in speed and efficiency, it makes up in setup time & cost. In other words, if you need 50 t-shirts of the same design, screen printing is the way to go. But, if you need 50 shirts, each with a different design, you just might want to follow in [RCLifeOn’s] footsteps.
Robot design traditionally separates the body geometry from the mechanics of the gait, but they both have a profound effect upon one another. What if you could play with both at once, and crank out useful prototypes cheaply using just about any old 3D printer? That’s where Interactive Robogami comes in. It’s a tool from MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) that aims to let people design, simulate, and then build simple robots with a “3D print, then fold” approach. The idea behind the system is partly to take advantage of the rapid prototyping afforded by 3D printers, but mainly it’s to change how the design work is done.
To make a robot, the body geometry and limb design are all done and simulated in the Robogami tool, where different combinations can have a wild effect on locomotion. Once a design is chosen, the end result is a 3D printable flat pack which is then assembled into the final form with a power supply, Arduino, and servo motors.
A white paper is available online and a demonstration video is embedded below. It’s debatable whether these devices on their own qualify as “robots” since they have no sensors, but as a tool to quickly prototype robot body geometries and gaits it’s an excitingly clever idea.
Once you fall deep enough into the rabbit hole of any project, specific information starts getting harder and harder to find. At some point, trusting experts becomes necessary, even if that information is hard to find, obtuse, or incomplete. [turingbirds] was having this problem with Bessel filters, namely that all of the information about them was scattered around the web and in textbooks. For anyone else who is having trouble with these particular filters, or simply wants to learn more about them, [turingbirds] has put together a guide with all of the information he has about them.
For those who don’t design audio circuits full-time, a Bessel filter is a linear, passive bandpass filter that preserves waveshapes of signals that are within the range of the filter’s pass bands, rather than distorting them in some way. [turingbirds]’s guide goes into the foundations of where the filter coefficients come from, instead of blindly using lookup tables like he had been doing.
For anyone else who uses these filters often, this design guide looks to be a helpful tool. Of course, if you’re new to the world of electronic filters there’s no reason to be afraid of them. You can even get started with everyone’s favorite: an Arduino.
A traditional quadcopter is designed to achieve 6 degrees of freedom — three translational and three rotational — and piloting these manually can prove to be a challenge for beginners. Hexacopters offer better stability and flight speed at a higher price but the flight controller gets a bit more complex.
Taking this to a whole new level, the teams at the Swiss Federal Institute of Technology (ETH Zürich) and Zurich University of the Arts (ZHDK) have come together to present a hexacopter with 6 individually tiltable axes. The 360-degree tilt in rotors allows for a whopping 12-degrees of freedom in flight and allows the UAV to fly in essentially any direction including parallel to walls.
In addition to the acrobatic capabilities of the design, the team has done some testing with autonomous control using external cameras. Their blog contains videos of their testing at various stages and it interesting to see the project evolve over a short span of nine months. Check out the video below of the prototype in action.
If you happened to look up during a drive down a suburban street in the US anytime during the 60s or 70s, you’ll no doubt have noticed a forest of TV antennas. When over-the-air TV was the only option, people went to great lengths to haul in signals, with antennas of sometimes massive proportions flying over rooftops.
Outdoor antennas all but disappeared over the last third of the 20th century as cable providers became dominant, cast to the curb as unsightly relics of a sad and bygone era of limited choices and poor reception. But now cheapskates cable-cutters like yours truly are starting to regrow that once-thick forest, this time lofting antennas to receive digital programming over the air. Many of the new antennas make outrageous claims about performance or tout that they’re designed specifically for HDTV. It’s all marketing nonsense, of course, because then as now, almost every TV antenna is just some form of the classic Yagi design. The physics of this antenna are fascinating, as is the story of how the antenna was invented.
Color palettes are key to any sort of visual or graphic design. A designer has to identify a handful of key colours to make a design work, making calls on what’s eye catching or what sets the mood appropriately. One of the problems is that it relies heavily on subjective judgement, rather than any known mathematical formula. There are rules one can apply, but rules can also be artistically broken, so it’s never a simple task. To this end, [Jack Qiao] created colormind.io, a tool that uses neural nets to generate color palettes.
It’s a fun tool – there’s a selection of palettes generated from popular media and sunset photos, as well as the option to generate custom palettes yourself. Colours can be locked so you can iterate around those you like, finding others that match well. The results are impressive – the tool is able to generate palettes that seem to blend rather well. We were unable to force it to generate anything truly garish despite a few attempts!
The blog explains the software behind the curtain. After first experimenting with a type of neural net known as an LSTM, [Jack] found the results too bland. The network was afraid to be wrong, so would choose values very much “in the middle”, leading to muted palettes of browns and greys. After switching to a less accuracy-focused network known as a GAN, the results were better – [Jack] says the network now generates what it believes to be “plausible” palettes. The code has been uploaded to GitHub if you’d like to play around with it yourself.