Projection Mapping in Motion Amazes

Projection mapping is pretty magical; done well, it’s absolutely miraculous when the facade of a building starts popping out abstract geometric objects, or crumbles in front of our very eyes. “Dynamic projection mapping onto deforming non-rigid surface” takes it to the next level. (Watch the video below.)

A group in the Ishikawa Watanabe lab at the University of Tokyo has a technique where they cover the target with a number of dots in an ink that is only visible in the infra-red. A high-speed (1000 FPS!) camera and some very fast image processing then work out not only how the surface is deforming, but which surface it is. This enables them to swap out pieces of paper and get the projections onto them in real time.

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A Spreadsheet For Guesswork

Ever wish you could guess more precisely? Or maybe just make your guesses look confusingly legitimate? Guesstimate could help.

It uses Monte Carlo simulations to add some legitimacy to the ranges given to it. For example, if you say the cost of lumber for your next project could be between 2 and 8 dollars a piece, you don’t typically mean that it’s equally likely to be any of those numbers. Most people mean that the boards are most likely to be around 3-5 dollars and everything lower or higher is less probable. Using different shaped distributions, Guesstimate can help include this discrepancy of thought into your pseudo-calculations.

It’s a neat bit of code with a nice interface. There is a commercial side to the project for those who want to collaborate openly or pay someone to host it privately. It has a few neat example models for those interested.

Does anyone use anything like this in their daily lives? Is there another similar project out there? This kind of thing is pretty cool!

Cellular Automata Explorer

Well all know cellular automata from Conway’s Game of Life which simulates cellular evolution using rules based on the state of all eight adjacent cells. [Gavin] has been having fun playing with elementary cellular automata in his spare time. Unlike Conway’s Game, elementary automata uses just the left and right neighbors of a cell to determine the next cell ahead in the row. Despite this comparative simplicity, some really complex patterns emerge, including a Turing-complete one.

[Gavin] started off doing the calculations by hand for fun. He made some nice worksheets for this. As we can easily imagine, doing the calculations by hand got boring fast. It wasn’t long before his thoughts turned to automating his cellular automata. So, he put together an automatic cellular automator. (We admit, we are having a bit of fun with this.)

This could have been a quick software project but half the fun is seeing the simulations on a purpose-built ecosystem. The files to build the device are hosted on Thingiverse. Like other cellular automata projects, it uses LED matrices to display the data. An Arduino acts as the brain and some really cool retro switches from the world’s most ridiculously organized electronics collection finish the look of the project.

To use, enter the starting condition with the switches at the bottom. The code on the Arduino then computes and displays the pattern on the matrix. Pretty cool and way faster than doing it by hand.

Yet Another Inductance Measuring Scheme

How do you measure the value of an unknown inductor? If you have an LCR bridge or meter, you are probably going to use that. If not, there are many different techniques you can use. All of them rely on the same thing my Algebra teacher Mr. Harder used to say back in the 1970’s: you have to use what you know to get what you don’t know.

[Ronald Dekker] must think the same way. He took a 50-ohm signal generator and a scope. He puts the signal output to about 20kHz and adjusts for 1V peak-to-peak on the scope. Then he puts the unknown inductor across the signal and adjusts the frequency (and only the frequency) for an output of 1/2 volt peak-to-peak.

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Fractals Among Us

Think not of what you see, but what it took to produce what you see

Benoit Mandelbrot

Randomness is all around you…or so you think. Consider the various shapes of the morning clouds, the jagged points of Colorado’s Rocky Mountains, the twists and turns of England’s coastline and the forks of a lightning bolt streaking through a dark, stormy sky. Such irregularity is commonplace throughout our natural world. One can also find similar irregular structures in biology. The branch-like structures in your lungs called Bronchi, for instance, fork out in irregular patterns that eerily mirror the way rivers bifurcate into smaller streams. It turns out that these irregular structures are not as irregular and random as one might think. They’re self-similar, meaning the overall structure remains the same as you zoom in or out.

The mathematics that describes these irregular shapes and patterns would not be fully understood until the 1970s with the advent of the computer. In 1982, a renegade mathematician by the name of Benoit Mandelbrot published a book entitled “The Fractal Geometry of Nature”.  It was a revision of his previous work, “Fractals: Form, Chance and Dimension” which was published a few years before. Today, they are regarded as one of the ten most influential scientific essays of the 20th century.

Mandelbrot coined the term “Fractal,” which is derived from the Latin word fractus, which means irregular or broken. He called himself a “fractalist,” and often referred to his work as “the study of roughness.” In this article, we’re going to describe what fractals are and explore areas where fractals are used in modern technology, while saving the more technical aspects for a later article.

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Star Track: A Lesson in Positional Astronomy With Lasers

[gocivici] threatened us with a tutorial on positional astronomy when we started reading his tutorial on a Arduino Powered Star Pointer and he delivered. We’d pick him to help us take the One Ring to Mordor; we’d never get lost and his threat-delivery-rate makes him less likely to pull a Boromir.

As we mentioned he starts off with a really succinct and well written tutorial on celestial coordinates that antiquity would have killed to have. If we were writing a bit of code to do our own positional astronomy system, this is the tab we’d have open. Incidentally, that’s exactly what he encourages those who have followed the tutorial to do.

The star pointer itself is a high powered green laser pointer (battery powered), 3D printed parts, and an amalgam of fourteen dollars of Chinese tech cruft. The project uses two Arduino clones to process serial commands and manage two 28byj-48 stepper motors. The 2nd Arduino clone was purely to supplement the digital pins of the first; we paused a bit at that, but then we realized that import arduinos have gotten so cheap they probably are more affordable than an I2C breakout board or stepper driver these days. The body was designed with a mixture of Tinkercad and something we’d not heard of, OpenJsCAD.

Once it’s all assembled and tested the only thing left to do is go outside with your contraption. After making sure that you’ve followed all the local regulations for not pointing lasers at airplanes, point the laser at the north star. After that you can plug in any star coordinate and the laser will swing towards it and track its location in the sky. Pretty cool.

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Make Math Real with this Analog Multiplier Primer

Remember learning all about functions in algebra? Neither do we. Oh sure, most of us remember linear plots and the magic of understanding y=mx+b for the first time. But a lot of us managed to slide by with only a tenuous grasp of more complex functions like exponentials and conic sections. Luckily the functionally challenged among us can bolster their understanding with this demonstration using analog multipliers and op amps.

[devttys0]’s video tutorial is a great primer on analog multipliers and their many uses. Starting with a simple example that multiplies two input voltages together, he goes on to show circuits that output both the square and the cube of an input voltage. Seeing the output waveform of the cube of a ramped input voltage was what nailed the concept for us and transported us back to those seemingly wasted hours in algebra class many years ago. Further refinements by the addition of an op amp yield a circuit that outputs the square root of an input voltage, and eventually lead to a voltage controlled resistor that can attenuate an input signal depending on its voltage. Pretty powerful stuff for just a few chips.

The chip behind [devttys0]’s primer is the Analog Devices AD633, a pretty handy chip to have around. For more on this chip, check out [Bil Herd]’s post on analog computing.

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