Glitching LED Display Proves Crowd Favorite

There’s something enchanting about the soft glow of a properly diffused LED, and this is only improved by greater numbers of LEDs. [Manoj Nathwani] was well aware of this, setting out to build a large display using ping-pong balls for their desirable optical qualities.Unfortunately, not everything went to plan, but sometimes that’s not all bad.

The matrix, built back in 2016 for EMF Camp, was sized at 32×18 elements, for a total of 576 pixels. This was achieved with the use of 12 WS2811 LED strips, with the lights set out on a 50mm grid. Cheap knock-off pingpong balls were used for their low cost, and they proved to be excellent diffusers for the LEDs.

With everything wired up to a NodeMCU, basic testing showed the system to be functioning well. However, once the full matrix was assembled in the field, things started to fall over. Basic commands would work for the first 200 LEDs or so, and then the entire matrix would begin to glitch out and display random colors. Unable to fix the problem in the field, [Manoj] elected to simply run the display as-is. Despite the problems, passers-by found the random animations to be rather beautiful anyway, particularly at night.

After the event, [Manoj] determined the issue was due to the excessive length of the data line, which in the final build was 48 meters long. While the problem may be rectified when [Manoj] revisits the project, the audience seemed to appreciate the first revision anyway.

LED displays will be a hacker staple until the heat death of the universe. Ping pong balls will also likely retain their position as a favorite diffuser. If you’ve got a great LED build of your very own, be sure to hit up the tips line!

Arduino Bot Rocks A PS2 Controller

As far as controlling robots goes, makers today are spoilt for choice. WiFi and Bluetooth enabled microcontrollers are a dime a dozen, and integration with smartphone apps is a cinch. Despite this, the old methods still hold sway, as [Igor Fonseca] demonstrates with a simple Arduino bot.

It’s a classic build, using a tracked chassis with a pair of motors providing propulsion and skid steering. The motors are controlled by an L298N H-bridge board, with power courtesy of a trio of 18650 batteries. An Arduino Uno acts as the brains of the operation. Control is via a Playstation 2 controller, in this case a 2.4 GHz third party version. This allows the robot to be controlled wirelessly, with the decoding handled by [Bill Porter]’s useful Arduino library.

It’s a cheap approach to building a remote-controlled bot, and one that would be a great way to teach interested children about how to work with embedded systems. We’ve featured a similar build before, too. Video after the break.

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Speed Up Filming With This Jawdropping 8-Axis Camera Crane

These days, it can feel like a project doesn’t exist unless you’ve posted a video on the Internet about it. [mingul] was in the process of producing his own videos, but found having to repeatedly move and set up the camera tiring. Naturally, a completely overkill eight-axis motion control robot was the solution. Video embedded below the break.

The scale of the build is something to behold. With 4.5 m travel on the X-axis, 6.5 m on the Y, and 2.1 m on the Z, it’s capable of traversing the full length of [mingul]’s workshop. Tilt, pan, and roll axes all feature 540 degrees of rotation, and there’s motors to control zoom and focus on the camera, too. Through software like Dragonframe, it’s possible to program complicated camera moves, and techniques like the classic dolly zoom are a cinch with such a versatile rig. It’s also possible to control the movement in real-time with a wireless Xbox controller.

[mingul] reports the build took a full three months of CNC machining, 3D printing and assembly. It’s a big step above a simple motorized camera slider, but we all have to start somewhere.

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Building Video Pong With Discrete Components

Pong is a classic from the very dawn of the video game era. Recreating it remains a popular exercise for those new to coding. However, its simple logic makes this game particularly suited to an all-hardware build; something which [Glen] tackles with aplomb.

Not content to take the easy way out, [Glen] went for a particularly hardcore method of construction. The game uses absolutely zero integrated circuits in its construction. Instead, it relies upon the services of 431 bipolar transistors, 6 JFETs and 826 diodes. Everything is laced together on protoboard, connected with a neatly organised nest of colored wires. Schematics are available for the curious.

It’s a full featured build, too. Video output is in color, scores are displayed at the top of the screen, and there’s even stereo panning for the sound effects. It just goes to show what some humble components can do when put to work in the right way. We’ve seen some of [Glen]’s work before too, for example in this op-amp bouncing ball device. Video after the break.

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Laser Crown Shines At Night

Sometimes you need something really flashy to complete an outfit. Whether it’s a sparkly pair of earrings or a stylish necklace, accessories are key to competing on the fashion battlefield. For those who want to bring some serious firepower, [p3nguin’s] laser crown might be just what the doctor ordered.

At the outset, we should state the crown only uses lasers in its construction, for cutting felt and acrylic. The light source is a Neopixel ring from Adafruit, capable of bringing the vibrant colors without risk of eye damage. The ring is then assembled with a series of snap-together acrylic parts and a felt cap, with slots for hair pins to keep the crown in place on the wearer’s head. A Trinket drives the show, with a LiPo battery used as a lightweight power supply.

It’s a nice build that’s sure to draw plenty of attention. We see some great wearables around these parts; this EL jacket is a particular favorite. Video after the break.

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Writing Characters Straight To The Linux Framebuffer

These days, working with a display in software is fairly easy. Thanks to the convenience of the modern OS, we’re blessed with graphical user interfaces, where things such as buttons and windows and text are all taken care of for us. Of course, once you start to wander off the beaten track, particularly in embedded systems with no GUI, things can get a little more difficult. For these situations, [JSBattista] wrote some code to blast text directly to the Linux framebuffer.

It’s a project borne out of necessity. Working with a Raspberry Pi with no X server, it was found that the console text size made it difficult to display data. By writing directly to the framebuffer, it would be possible to display text of a larger size without having to implement a full GUI, and overheads could be kept to a minimum.

Working in this manner comes with some limitations. Glyphs are taken from an array in bitmap format, rather than font files. In this case, a font akin to that of the Alien sentry gun interface was chosen, for an attractive sci-fi look. Lowercase characters are currently unimplemented. Testing thus far has been on Raspberry Pi and Beaglebone non-GUI systems, with performance varying depending on platform.

It’s a project we suspect might prove useful to the developers of lightweight embedded systems. It’s something that may take some tweaking and experimentation to implement, but the hacker set rarely shy away from a challenge. If you’re eager to get down and dirty with some heavy programming, this tutorial on Linux graphics will help.

Name Stone Helps You Greet Coworkers

When starting a new job, learning coworkers names can be a daunting task. Getting this right is key to forming strong professional relationships. [Ahad] noted that [Marcos] was struggling with this, so built the Name Stone to help.

The Name Stone consists of some powerful hardware, wrapped up in a 3D printed case reminiscent of the Eye of Agamotto from Doctor Strange. Inside, there’s a Jetson Nano – an excellent platform for any project built around machine learning tasks. This is combined with a microphone and camera to collect data from the environment.

[Ahad] then went about training neural networks to help with basic identification tasks. Video was taken of the coworkers, then the frames used to train a convolutional neural network using PyTorch. Similarly, a series of audio clips were used to again train a network to identify individuals through the sound of their voice, using MFCC techniques. Upon activating the stone, the device will capture an image or a short sound clip, and process the data to identify the target coworker and remind [Marcos] of their name.

It’s a project that could be quite useful, given to new employees to help them transition into the new workplace. Of course, pervasive facial recognition technology does have some drawbacks. Video after the break.

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