Space is big. Really big. Yet on TV and movies, enemy spacecraft routinely wind up meeting at roughly the same spot and, miraculously, in the same orientation. If you’ve ever tried to find something smaller than the moon in a telescope, you’ll appreciate that it isn’t that easy. There are plenty of tricks for locating objects ranging from expensive computerized scopes with motors to mounting a phone with Google Sky or a similar program to your telescope. [DentDentArthurDent] didn’t use a phone. He used an Arduino with an outboard GPS module.
You still have to move the scope yourself, but the GPS means you know your location and the time to a high degree of accuracy. Before you start an observing session, you simply point the telescope at Polaris to calibrate the algorithm, a process which in the northern hemisphere is pretty easy.
The telescope in question is a Dobson, so is easy to move and easy to sense its position using potentiometers and an A/D. The project also includes a detailed description of the math used to convert the time, latitude, longitude, right ascension, and declination into position data. One of four LEDs show if you should move up, down, left, or right. When you are on target, all four LEDs light. We assume you should use red LEDs and a red LCD filter so you don’t ruin your night vision.
There are a few sources of error and [Arthur] does a great job of analyzing and correcting each one. The project even has a nice 3D printed case. The database only contains 45 objects but it is easy to add more. We wondered if it wouldn’t have been better to use a larger computer such as a Raspberry Pi to get the stellar data — maybe even from the Internet — and rely on the Arduino to just manage the position sensing and direction indication, but then again, this works and it is very inexpensive.
Last year, Google released an artificial intelligence kit aimed at makers, with two different flavors: Vision to recognize people and objections, and Voice to create a smart speaker. Now, Google is back with a new version to make it even easier to get started.
The main difference in this year’s (v1.1) kits is that they include some basic hardware, such as a Raspberry Pi and an SD card. While this might not be very useful to most Hackaday readers, who probably have a spare Pi (or 5) lying around, this is invaluable for novice makers or the educational market. These audiences now have access to an all-in-one solution to build projects and learn more about artificial intelligence.
Modular synthesizers are some of the ultimate creative tools for the electronic musician. By experimenting with patch leads, knobs and switches, all manner of rhythmic madness can be conjured out of the æther. While they may overflow with creative potential, modular synths tend to fall down in portability. Typically built into studio racks and composed of many disparate modules, it’s not the sort of thing you can just take down the skate park for a jam session. If only there was a solution – enter the madness that is Synth Bike.
Synth Bike, here seen in the 2.0 revision, impresses from the get go, being built upon a sturdy Raleigh Chopper chassis. The way we see it, if you’re going to build a synth into a bicycle, why not do it with some style? From there, the build ratchets up in intensity. There’s a series of sequencer modules, most of which run individual Arduino Nanos. These get their clock from either a master source, an external jack, or from a magnetic sensor which picks up the rotation of the front wheel. Your pace dictates the tempo, so you’ll want to work those calves for extended raves at the park.
The features don’t stop there – there are drums courtesy of a SparkFun WAV Trigger, an arcade button keyboard, and a filter board running the venerable PT2399 digital delay chip. It’s all assembled on a series of panels with wires going everywhere, just like a true modular should be.
The Nintendo Switch portable gaming system is heavily locked down to prevent hacking, but the Labo add-on looks like it might be a different matter. The Labo is a series of add-on devices made of cardboard that does things like turn the Switch into a musical keyboard that plays a waveform on a card that you slot in. [Hunter Irving] decided to try a bit of reverse engineering on these cards to see if he could 3D print his own. Spoilers: he could.
[Hunter] started by taking one of the cards that come with the Labo and looking at the layout. These cards are, like the rest of the Labo, very simple: they are just shaped pieces of card that fit into the back of the keyboard add-on. When you press a button, the Switch camera reads the card to create the waveform. So, the process involved figuring out the required dimensions of the card to create a template. [Hunter] then created simple waveforms (square, sine, sawtooth) in Inkscape, and used this to create a 3D printable waveform card. A quick bit of 3D printing later, he had several cards ready, and these worked without problems. As well as the synthetic waveforms, he tried real ones, such as an organ, taking the waveform shape from the zoomed-in sample and using that to print. This post describes the process nicely and offers downloads of 9 sample cards and a template to create your own.
We suspect that this is only scratching the surface of what can be done with the Switch, Labo, and some ingenuity. Unlike the Switch itself, the Labo seems to be built for hacking, using simple, easy to use components to create surprisingly complex mechanisms that could be adapted for any number of purposes.
The PDP-11 is perhaps the most important computer in history. This was the king of all minicomputers, and once you get past the amazing front panels of the 11/20, 11/40, and 11/70, you’ll find PDP-11s everywhere. Heathkit sold one. It was the smallest computer that could run Unix. There were desktop versions sold as DEC Professionals. I have been told Ticketmaster — the entire backend of all event ticket sales in the United States — still runs on PDP-11s.
One of the interesting bits of the PDP-11 is the miniaturization that happened over the course of its development. Over time, the Unibus processor cards of the earlier models were shrunk down into a single chip. This PDP-on-a-chip was then cloned by the Soviets, and like most vintage Eastern European electronics, they’re all readily available on eBay.
For his Hackaday Prize entry, [SHAOS] is taking one of these chips and turning it into a modern machine. The PDPii is a project to bring the PDP-11 back to life in the form of an Open Source motherboard with a Mini-ITX motherboard. Is it game-changing? No, not really; you could buy a desktop PDP-11 thirty years ago. This project, though, is taking new old stock chips you can buy for ten dollars and turning it into something resembling a modern system. Finally, Ticketmaster can upgrade.
The design of this project doesn’t quite meet the spec for the Mini-ITX form factor; it’s based off the RC2014 backplane Z80 computer, but desktop computer cases are cheap, as are power supplies, and I’m sure someone out there knows how to fit an eight inch floppy in a five and a quarter inch hole.
The key feature for this Mini-ITX backplane PDP-11 is a redesign of the Q-bus found in later PDPs to something that’s a bit smaller, a bit cheaper to manufacture, and still has all the relevant pins accessible. With some reconfiguring of the baroque DEC standards, [SHAOS] came up with the Bread-Board Friendly Q-bus Extended, or BBQ-Bus+. The next step for this project is gathering up a few PDP-11 compatible Russian КР1801ВМ2 CPUs and going to town on the architecture of what is probably the most replicated computer design ever.
Arduino 101 is getting an LED to flash. From there you have a world of options for control, from MOSFETs to relays, solenoids and motors, all kinds of outputs. Here, we’re going to take a quick look at some inputs. While working on a recent project, I realized the variety of options in sensing something as simple as whether a light is on or off. This is a fundamental task for any system that reacts to the world; maybe a sensor that detects when the washer has finished and sends a text message, or an automated chicken coop that opens and closes with the sun, or a beam break that notifies when a sister has entered your sacred space. These are some of the tools you might use to sense light around you.
Also called the Light Dependent Resistor (LDR) a photoresistor is exactly what it sounds like; a resistor that changes resistance when exposed to light. This is probably the easiest to use and the hardest to break, so it’s great for beginners. Made from (usually) cadmium sulfide, it changes resistance from hundreds of thousands of ohms in the dark to hundreds of ohms in the light.
Hooking one up is as easy as creating a basic voltage divider circuit. You can then do an analogRead on the pin and watch how the value changes when the light level changes. This option is ideal for simple circuits where you are trying to detect the presence of visible or infrared light, but it’s very slow to react (hundreds of milliseconds), so it’s not good for data transmission.
The photodiode, also appropriately named, is a diode that changes the amount of current that passes through it with the amount of light. It can be used in two different ways. The easy one is photovoltaic mode, where the photodiode is exposed to light, the energy of the photons excites electrons which generate a voltage that you can measure to sense light level, or collect as in a solar cell. The other is photoconductive mode, where the diode is reverse biased. Without getting into the exact physics, this mode has faster response times, making it more useful for data transmission using light (like an IR receiver).
All diodes are photodiodes to some extent; some are just shielded better. Many remote control sensors will have a filter on it to allow only a narrow band of light through. Even an LED can work backwards, though not very well. The high level of variability makes it less than ideal for production or larger applications, but for a one-off it’s pretty slick. We covered the idea of LEDs as light sensors a couple years ago. We also saw that with the Raspberry Pi 2, a particular diode would reset the pi when exposed to bright light.
If a photodiode converts light into current, then the next step is pretty easy. A transistor uses the amount of current at the base to control flow of electricity between the collector and emitter. Put the two together, and you have the photodiode acting as the base to control the transistor. The phototransistor can be either active, where the amount of light changes the amount of current flow in the transistor, or switched, where there is a threshold above which the transistor is on and below which it is off.
Phototransistors are used in remote control receivers because they are fast, easy to use, and made to filter out all but a very narrow light frequency range. Technically, the photodiode is faster, but both work well for IR receivers, and the phototransistor has the added benefit of gain, meaning it can achieve longer range. Consumer IR signals usually work on a carrier frequency between 36 kHz and 40 kHz, and phototransistors have switching frequencies up into the hundreds of kHz, making them ideal for this application. In this basic example, one IR LED is hooked up to a microcontroller, and a phototransistor is hooked up to a separate microcontroller, with only air between them. There are a variety of libraries available to do the communication, but from an electronics standpoint, this is the basic circuit.
Also known as the optocoupler, this is a clever device that combines a light source and a light sensor into a single package. If you’re familiar with ground loops, you’ll know what a pain it is to have two separate systems that are electrically connected. Sometimes it’s really nice to isolate the two, but still allow them to talk to each other. This is done with an optoisolator, which has an LED and a phototransistor or photodiode inside it. One system powers the LED, and the other system watches the phototransistor.
These are very handy if you have a high voltage system to which you have access, but don’t want to risk blowing anything up by connecting your Arduino to it to monitor status. These can be both digital (on/off) and analog (range of values), based on the application. You can easily make your own optocoupler by combining an LED and a photoresistor or photodiode or phototransistor together inside a light-proof case. The circuit is exactly the same as the previous circuit.
You’ve seen them on your calculator and roof. These convert photons into electrons and generate a small voltage. It’s the same as a photodiode in photovoltaic mode because that’s exactly what it is. The only difference is surface area. For calculators, a small surface area can be enough to power the calculator (or charge up a capacitor or battery for short bursts). By sensing the voltage on the cell, it’s possible to detect the light level. Your outdoor light sensor could just include a photovoltaic cell, ESP8266, and battery!
Just detecting the presence of light is sometimes not enough. Sometimes you need to know what color the light is. If you are looking for a specific frequency you can take a photoresistor and cover it with a colored gel and call it mostly good (except for white light, which would contain all the frequencies). This one-pixel camera is best suited for things like sorting M&Ms and Skittles, and is often found on assembly lines or other sorting tools. There are two ways to make a color sensor. The first is with a single photodiode and RGB LEDs. You turn on the red, capture the photodiode value, switch to the green and capture the value, and switch to the blue and capture that value. A red thing will have a high red photodiode value and low other values. This scanning approach is slow, though, so the other method is to have three photodiodes and a white light, with colored filters over each of the photodiodes. This way a reading of all three colors can be taken simultaneously. The photodiode will respond differently to the different parts of the spectrum, so some calibration after the reading is necessary.
Here is a typical application circuit for a color sensor IC (The BH1745NUC from Rohm). It has 4 photodiodes, three of which are behind red, green, and blue filters. Those are then fed through an ADC and presented to a microcontroller via an I2C interface. Most color sensors do this because they handle the color calibration within the package.
We have photo sensitive resistors, diodes, and transistors so far. How about capacitors? The charge-coupled device (CCD) is the thing in your camera that captures an image, or the line on your scanner. It’s made of an array of tiny pixels, each of which has a tiny light-sensitive capacitor. When light hits it, a stored charge is built up, creating a voltage. Then a series of shift registers scans through the array of capacitors and measures the voltage levels, which correspond to light levels at each pixel. The bigger the array, and the more dense the pixels, the higher the resolution of the camera.
If you want to capture color images, you have two options. The first is to take a black and white camera, then bathe your subject in red light and take a picture, bathe it in green light and take a picture, and bathe it in blue light and take a picture, then combine those three images into one with each image representing a different channel. The other option is to get a CCD with three times as many sensors, each covered with a colored filter, and take a single photograph. We covered the technology behind CCDs in much more detail already, but the gist is that you use them for capturing images.
Which one is right for you?
Of course, it all depends on your application. For detecting simple light levels, go with the photoresistor. They are super simple, cheap, and robust. If you need something faster for signalling, upgrade to the phototransistor, which is not quite as fast as the photodiode, but the extra gain makes it easier to integrate into your project. For keeping your electronics separate from other electronics, use an optoisolator. If you need to do facial recognition to identify your dog to allow it through the dog door, use a CCD and send us a tip when you’ve completed the project. Bonus points if you use a large two-dimensional array of photoresistors to make a very slow low-resolution camera.
For some of us here at Hackaday, school is but a very distant memory. All that teenage awkwardness we’d rather forget, synth pop, and 8-bit computers were cool the first time around, and our newer classrooms didn’t have blackboards any more. The Whiteboard Future Had Arrived, and it came with solvent-laden pens that our more rebellious classmates swore would get you high if you sniffed them for long enough. Innocent times. Kids nowadays probably get their lessons from iPads, but the whiteboard isn’t finished just yet. [f4hdk] has updated his board with Scribot, a whiteboard-writing robot arm driven by a couple of stepper motors and a nicely-engineered set of belts, that writes text from ASCII files in a custom-designed vector font.
At the end of the arm is a whiteboard marker, and in a neat twist it has an eraser on its rear end. A quick flip of the servo holding the marker, and it can rub out any of its work. Behind it all is an LPC1789 Cortex M3-based Mbed board with appropriate servo driver boards, and for those curious enough to take a second look there is a full code repository. The result as you can see in the video below the break is a very well-executed whiteboard writer. Your 1980s teacher might have grumbled at the new technology, but certainly couldn’t accuse it of doing a bad job!
Levers are literally all around us. You body uses them to move, pick up a pen to sign your name and you’ll use mechanical advantage to make that ballpoint roll, and that can of soda doesn’t open without a cleverly designed lever.
I got onto this topic quite by accident. I was making an ornithopter and it was having trouble lifting its wings. For the uninitiated, ornithopters are machines which fly by flapping their wings. The problem was that the lever arm was too short. To be honest, as I worked I wasn’t even thinking in terms of levers, and only realized that there was one after I’d fine-tuned its length by trial and error. After that, the presence of a lever was embarrassingly obvious.
I can probably be excused for not seeing a lever right away because it wasn’t the type we most often experience. There are different classes of levers and it’s safe to say that most people aren’t even aware of this. Let’s take a closer look at these super useful, and sometimes hidden mechanisms known as levers.
Levers Are One of the Oldest Mechanisms
Technically speaking, levers predate humanity. You find them in biology — your forearm is a good example which I’ll go into later in the article.
When it comes to man made mechanisms, levers are suspected to have been used as long ago as Ancient Egypt for lifting large block and obelisks but the earliest writings of their working principle come from followers of Aristotle and from Archimedes, both dated around 300 BC. Archimedes gave this static description of it:
Magnitudes are in equilibrium at distances reciprocally proportional to their weights.
He also famously said, “Give me a place to stand on, and I will move the Earth.” Putting this into practice, he’s reputed to have devised a defensive weapon called the Claw for fighting off ships attacking city walls. Historical accounts seem to describe a crane sitting on the wall which lowers a grappling hook onto attacking ships and lifts them out of the water, capsizing or sinking them.
As shown here, a lever consists of a beam which pivots on a fulcrum. A force, called the effortFe is applied at some distance a from the fulcrum. And a load Fl exists at some distance b from the fulcrum.
The law of the lever states that:
The ratio of the force at the load to the effort force is equal to the ratio of the distances of those forces from the fulcrum.
Mathematically, it can be stated as:
MA = Fl/Fe = a/b
MA stands for Mechanical Advantage and is a measure of how much the force is amplified. The formula shows that if length a from the fulcrum to the effort is greater than length b from the fulcrum to the load, then the mechanical advantage will be greater than one.
Note that we’re not talking about free energy here. The power input is equal to the power output, ignoring losses due to friction, wear, and bending of the lever beam. Power is force multiplied by velocity and they differ proportionately from each other. If a > b then the load will move more slowly than the point where the effort is applied (which must move a greater distance in the same amount of time).
Classes of Levers
Levers can be arranged in different ways and are described in three classes, all of which follow the law of the lever.
Class 1 Levers
Class 1 is perhaps the most familiar. Examples of that are a seesaw, a crowbar as well as any time you’ve picked up a stick and placed it on a handy pivot point to lift something heavy at the other end of the stick. A pair of pliers are class 1 levers which we use very often but rarely recognize them as such.
Class 2 Levers
With a Class 2 lever, the fulcrum is moved to one end of the lever, with the load in the middle and the force at the other end. Every time you pick up a wheelbarrow you use a class 2 lever, with the wheel’s axle is the fulcrum.
Class 3 Levers
The arrangement of the class 3 lever can be the most difficult to visualize. The fulcrum is still at one end of the lever, but the effort is now in the middle, with the load at the opposite end. It’s harder to think of everyday class 3 examples but we’ll see three of them below. When we look at an exoskeleton arm, a human arm, and a rubber band driven ornithopter wing we’re viewing class 3 levers.
James’ Exoskeleton Levers
I searched for a great example of a lever in a hacker made project and came up with a great one by our very own [James Hobson]. He built an exoskeleton with arms for lifting heavy loads. Interestingly, each arm contained both a class 1 and a class 3 lever.
The arm is actuated by pistons. The main difference between class 1 and class 3 levers is that the load and the fulcrum have been switched. Here you can see that the location of the rear piston creates a class 1 lever, the location of the front piston creates a class 3 lever. You can see him use the rig to curl a 170 pound barbell.
Levers In The Human Body
With all its muscles, bones, and joints, it should be no surprise that the human body makes abundant use of levers.
However, they’re not always used for mechanical advantage. In the case of lifting a load by raising the lower arm and using the elbow as the fulcrum, the effort is provided by a muscle in the upper arm. This muscle is attached to the lever (the bone) very close to the fulcrum, meaning that a is short compared to b, which extends from the fulcrum to the load in the hand (in the diagram, R stands for Resistance). Therefore the mechanical advantage a / b is less than one.
Instead, the benefit here is that a small movement of the bone at the muscle produces a large movement at the hand. This makes for a compact and agile arm which can be useful in tight spaces. A lifting muscle which instead extends from the shoulder to near the wrist would get in the way much of the time. Note that James has done a similar thing with his exoskeleton arm, though he added the second piston to push while the other pulls/lifts.
The Ornithopter’s Lever
The typical rubber band powered ornithopter has a fuselage running down the middle that acts as the main body to which all the parts are connected. At the bottom of the ornithopter’s fuselage is a crank which is turned by a twisted rubber band. Connecting rods connect the wings to the crank. Turning the crank raises and lowers the wings through the connecting rods. This raising and lowering can be seen clearly in the animated GIF.
Looking at the diagrams, the fulcrum is in the middle of the ornithopter, at the top of the fuselage. It’s there where each wing pivots as they flap up and down.
The load is actually the air pressing on a wing membrane as the wing is pushed up or pulled down, though my issue was most evident when pushing up.
The effort is applied from below, where the connecting rods connect to each wing.
The non-obvious lever in my ornithopter turned out to be a combination of two different classes of levers, a class 2 and 3 lever, both of which exist in each wing.
Class 2 Lever
The class 2 lever is the section from the fulcrum to where the effort is applied by the connecting rod connected to the wing. The load which makes it a class 2 lever is the air pressure on the section of wing extending back between those two points. This fits the definition of a class 2 lever because the load is in the middle, between the fulcrum and the effort.
Class 3 Lever
The class 3 lever is again formed by the fulcrum and the effort at the connecting rod, but the load is the air pressure on the wing on the side farther from the effort in the opposite direction of the fulcrum. This fits the definition of a class 3 lever because the effort is in the middle, between the load and the fulcrum.
Seeing Levers Everywhere
So while levers don’t always stand out, they are found in a large number of places. That’s doubtless due to how useful they are. We’d like to hear in the comments below where you’ve used levers or which surprising places you’ve found them in.
If you’re anything like us, you feel slightly guilty when you send a job to a printer only to find that twenty pages have printed wrong. Maybe it’s a typo, maybe it’s the dreaded landscape versus portrait issue. Whatever it is, trees died for your mistake, and there’s nothing you can do about it except to recycle the waste. But first, wipe that guilt away by using this one-stroke paper airplane maker to equip the whole office for an epic air battle.
We have to admit, automated paper handling has always fascinated us. The idea that a printer can reliably (sometimes) feed individual sheets of a stack is a testament to good design, and don’t even get us started about automatic paper folding. [Jerry de Vos]’ paper airplane maker doesn’t drive the sheets through the folder — that’s up to the user. But the laser-cut plywood jig does all the dirty work of creating a paper airplane. The sheet is clipped to an arm that pulls the paper through a series of ramps and slots that force the paper gently into the five folds needed for the classic paper dart. It’s fascinating to watch, and even though everyone seems to be using it very gingerly lest the paper tear, we can see how adding some rollers and motors from a scrapped printer could entirely automate the process. Think of the fun a ream of paper could provide around the office then.
Neural networks are a core area of the artificial intelligence field. They can be trained on abstract data sets and be put to all manner of useful duties, like driving cars while ignoring road hazards or identifying cats in images. Recently, a biologist approached AI researcher [Janelle Shane] with a problem – could she help him name some tomatoes?
It’s a problem with a simple cause – like most people, [Darren] enjoys experimenting with tomato genetics, and thus requires a steady supply of names to designate the various varities produced in this work. It can be taxing on the feeble human brain, so a silicon-based solution is ideal.
[Janelle] decided to use the char-rnn library built by [Andrej Karpathy] to do the heavy lifting. After training it on a list of over 11,000 existing tomato varieties, the neural network was then asked to strike out on its own.
The results are truly fantastic – whether you’re partial to a Speckled Garfech or you prefer the smooth flavor of the Golden Pow, there’s a tomato to suit your tastes. When the network was retrained with additional content in the form of names of metal bands, the results get even better – it’s only a matter of time before Angels of Saucing reach a supermarket shelf near you.