Those Bullet Effects In Terminator 2 Weren’t CGI

November 14, 2021 by 25 Comments

Remember Terminator 2? Guns were nearly useless against the murderous T-1000, played by Robert Patrick. Bullets fired at the “liquid metal” robot resulted only in a chrome-looking bullet splash that momentarily staggered the killing machine. The effects were done by Stan Winston, who died in 2008, but a video and short blurb shared by the Stan Winston School of Character Arts revealed, to our surprise and delight, that the bullet impact effects were not CGI.

How was this accomplished? First of all, Winston and his team researched the correct “look” for the splash impacts by firing projectiles into mud and painstakingly working to duplicate the resulting shapes. These realistic-looking crater sculpts were then cast in some mixture of foam rubber, and given a chromed look by way of vacuum metallizing (also known as vacuum deposition) which is a way of depositing a thin layer of metal onto a surface. Vacuum deposition is similar to electroplating, but the process does not require the object being coated to have a conductive surface.

These foam rubber splash patterns — which look like metal but aren’t — were deployed using a simple mechanical system. A variety of splashes in different sizes get individually compressed into receptacles in a fiberglass chest plate. Covering each is a kind of trapdoor, each held closed by a single pin on a cable.

To trigger a bullet impact effect, a wireless remote control pulls a cable, which pulls its attached pin, and the compressed splash pattern blossoms forth in an instant, bursting through pre-scored fabric in the process. Sadly there are no photos of the device itself, but you can see it in action in the testing video shared by the Stan Winston School, embedded below.

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A robot that uses CV to detect villagers in Stardew Valley and display their gift preferences on a screen.

Stardew Valley Preferences Bot Is A Gift To The Player

November 14, 2021 by 1 Comment

It seems like most narrative games have some kind of drudgery built in. You know, some tedious and repetitious task that you absolutely must do if you want to succeed. In Stardew Valley, that thing is gift giving, which earns you friendship points just like in real life. More important than the giving itself is that each villager has preferences — things they love, like, and hate to receive as gifts. It’s a lot to remember, and most people don’t bother trying and just look it up in the wiki. Well, except for Abigail, who seems to like certain gemstones so much that she must be eating them. She’s hard to forget.

[kutluhan_aktar]’s villager gift preferences bot is a fun and fantastic use of OpenCV. This bot uses a LattePanda Alpha 864s, which is a single-board computer with an Arduino Leonardo built in. It works using template matching, which is basically a game of Where’s Waldo? for computers.

Given a screenshot of each villager in various positions, the LattePanda recognizes them among a given game scene, then does a lookup of their birthday and preferences which the Leonardo prints on a 3.5″ LCD screen. At the same time, it alerts the player with a buzz and big green LED. Be sure to check it out in action after the break.

In Animal Crossing, the drudgery amounts to pressing the A button while catching shooting stars. That’s not a huge problem for a Teensy.

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a money shot of the hidden arcade

Arcade Machine Pack And Play

November 14, 2021 by 3 Comments

There’s something about the large imposing wooden box of an arcade machine that lends a confident presence to a room. The problem with a tall and heavy box is that it takes up quite a bit of space and readily draws the eye. So [Alexandre Chappel] set out to avoid that and build an arcade machine that could hide in plain sight.

Extra points awarded for neat wiring on the inside.

The idea is a wooden box hung on the wall that folds up when not in use. [Alex] starts with Baltic birch plywood cut into the panels. Next, he applies edge banding (a thin veneer with some glue on the backside) so that all the exposed edges look like natural wood. Next, a screen hole is routed into the face frame, allowing an LCD monitor to sit snuggly in. A combination of pocket holes and biscuits allows [Alex] to assemble everything with no visible screws or fasteners.

With the help of a 3D printer, he quickly fabricated a locking mechanism to keep the front panel attached when it folds up. The hinge is also 3D printed. The typical Raspberry Pi 4 powers this particular machine. Two french cleats hold the box onto the wall, and once the system is on the wall, we have to say it looks incredible.

If you’re looking for a smaller but more traditional arcade cabinet, why not take a look at this arcade cabinet for toddlers? Or, if you loved the solid wood look of the hidden arcade, this full-sized solid oak cabinet would be something you would enjoy. Video after the break.

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Chipboard prototype of a wireless phone charger with style.

Prototyping Your Way To Better Prototypes

November 13, 2021 by 13 Comments

If you’ve ever made a prototype of something before making the “real” one or even the final prototype, you probably already know that hands-on design time can’t be beat. There’s really no substitute for the insight you will glean from having a three-dimensional thing to hold and turn over in your hands for a full assessment. Sometimes you need to prototype an object more than once before investing time, money, and materials into making the final prototype for presentation.

This is [Eric Strebel]’s second video in series about making an eco-friendly wireless phone charger. He made a paper prototype in the first video, and in this follow-up, he refines the idea further and makes a chipboard version of the charger before the final molded paper pulp prototype. The main advantage of the chipboard version is to design the parts so that each one will be easier to pull from its mold in a single piece without any undercuts.

By building the chipboard version first, [Eric] is able to better understand the manufacturing and assembly needs of this particular widget. This way, he can work out the kinks before spending a bunch of time in CAD to create a 3D-printed mold and making the paper pulp prototype itself. He emphasizes that this process is quite different from the 2.5D method of laser-cutting a single piece of chipboard and folding it up into a 3D object like it was a cereal box, which is likely to hide design issues. Be sure to check out the video after the break.

We think this prototype is quite nice-looking, and believe that everything deserves good design. Why should a wireless charger be any different? [Eric] has prototyped in a lot of media, but he seems especially skilled in the art of foam core board. Start with the masterclass and you’ll have a better appreciation for his foam armored vehicle and one of the many ways he smooths out foam parts.

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Bluetooth RC Car Packs In A Few Sensors

November 13, 2021 by 4 Comments

Have you ever been walking around the house, desperate to know the ambient temperature, humidity, and barometric pressure? Have you ever wanted to capture that data with a small remote-controlled platform? If so, this project from [TUENHIDIY] will be exactly what you’ve been looking for. 

The little remote-control car is built around a Seeed Wio Terminal. This is a microcontroller platform that comes with a screen already attached, along with wireless hardware baked in and Grove connectors for hooking up external modules. Thus, the car adds a DHT11 temperature and humidity sensor, along with a BMP280 air pressure sensor using the Grove connectors.

Driving the car is done via a Blynk smartphone app that communicates with the Wio Terminal. Small DC motors at each wheel are driven via a DFRobot quad-motor shield. With the built-in screen, the RC car displays commands received from the smartphone app, as well as the temperature, humidity and pressure in the immediate environment.

We really like the simple PVC-based chassis design, and it’s a straightforward project that demonstrates how to build a Bluetooth-controlled car. Data collected by the sensors is also visible on the smartphone app, so if you need to sample conditions in the next room without getting off the couch, you could do that pretty easily.

Projects like these are a good way to get familiar with working with motors and sensors. It’d be a great base for simple robotics development, too. We’ve featured builds from [TUENHIDIY] before, too, like this great rotary plotter that can draw on bottles. Video after the break.

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Mini-lathe carriage wheel

Improving A Mini-Lathe With A Few Clever Hacks

November 13, 2021 by 21 Comments

Like many budget machinists, the delightfully optimistically named [We Can Do That Better] had trouble with some of the finer controls on his import mini-lathe. But rather than suffer through it, he chose to rectify the machine’s shortcomings and in the process, teach everyone a bunch of great tips.

[We Can Do That Better]’s lathe retrofit focused on the carriage handwheel, which appears to lack proper bearings and wobbles around in a most imprecise manner. On top of that, the gearing of the drive made for an unsatisfying 19 mm of carriage travel per revolution of the handwheel. A single gear change made that an even 20 mm per rev, which when coupled with a calibrated and indexed handwheel ring greatly simplifies carriage travel measurements.

While the end result of the build is pretty great in its own right, for our money the best part of the video is its rich collection of machinist’s tips. The use of a wooden dowel and a printed paper template to stand in for a proper dividing head was brilliant, as was using the tailstock of the lathe to drive an engraving tool to cut the index lines. We’ve seen the use of a Dremel tool mounted to the toolpost to stand in for a milling machine before, but it’s always nice to see that trick used. And the mechanism for locking the dial to the handwheel was really clever, too.

Considering a mini-lathe? As encouraging as [We Can Do That Better]’s experience may be, it might be wise to take a deep dive into the pros and cons of such a machine.

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OpenGL Machine Learning Runs On Low-End Hardware

November 13, 2021 by 16 Comments

If you’ve looked into GPU-accelerated machine learning projects, you’re certainly familiar with NVIDIA’s CUDA architecture. It also follows that you’ve checked the prices online, and know how expensive it can be to get a high-performance video card that supports this particular brand of parallel programming.

But what if you could run machine learning tasks on a GPU using nothing more exotic than OpenGL? That’s what [lnstadrum] has been working on for some time now, as it would allow devices as meager as the original Raspberry Pi Zero to run tasks like image classification far faster than they could using their CPU alone. The trick is to break down your computational task into something that can be performed using OpenGL shaders, which are generally meant to push video game graphics.

An example of X2’s neural net upscaling.

[lnstadrum] explains that OpenGL releases from the last decade or so actually include so-called compute shaders specifically for running arbitrary code. But unfortunately that’s not an option on boards like the Pi Zero, which only meets the OpenGL for Embedded Systems (GLES) 2.0 standard from 2007.

Constructing the neural net in such a way that it would be compatible with these more constrained platforms was much more difficult, but the end result has far more interesting applications to show for it. During tests, both the Raspberry Pi Zero and several older Android smartphones were able to run a pre-trained image classification model at a respectable rate.

This isn’t just some thought experiment, [lnstadrum] has released an image processing framework called Beatmup using these concepts that you can play around with right now. The C++ library has Java and Python bindings, and according to the documentation, should run on pretty much anything. Included in the framework is a simple tool called X2 which can perform AI image upscaling on everything from your laptop’s integrated video card to the Raspberry Pi; making it a great way to check out this fascinating application of machine learning.

Truth be told, we’re a bit behind the ball on this one, as Beatmup made its first public release back in April of this year. It might have flown under the radar until now, but we think there’s a lot of potential for this project, and hope to see more of it once word gets out about the impressive results it can wring out of even the lowliest hardware.

[Thanks to Ishan for the tip.]