There’s a great deal of research happening around the topic of autonomous vehicles of all creeds and colours. [Ryan] decided this was an interesting field, and took on an autonomous drone as his final project at Cornell University.
The main idea was to create a drone that could autonomously follow a target which provided GPS data for the drone to follow. [Ryan] planned to implement this by having a smartphone provide GPS coordinates to the drone over WiFi, allowing the drone to track the user.
As this was a university project, he had to take a very carefully considered approach to the build. Given likely constraints on both money and time, he identified that the crux of the project was to develop the autonomous part of the drone, not the drone itself. Thus, off-the-shelf parts were selected to swiftly put together a drone platform that would serve as a test bed for his autonomous brain.
The write up is in-depth and shares all the gritty details of getting the various subsystems of the drone talking together. He also shares issues that were faced with altitude control – without any sensors to determine altitude, it wasn’t possible to keep the drone at a level height. This unfortunately complicated things and meant that he didn’t get to complete the drone’s following algorithm. Such roadblocks are highly common in time-limited university projects, though their educational value cannot be overstated. Overall, while the project may not have met its final goals, it was obviously an excellent learning experience, and one which has taught him plenty about working with drones and the related electronics.
For another take on autonomous flight, check out this high-speed AI racing drone.
[Avidan Ross] has an unyielding passion for coffee. Brewing a proper espresso is more than measuring fluid ounces, and to that end, his office’s current espresso machine was not making the cut. What’s a maker to do but enlist his skills to brew some high-tech coffee.
For a proper espresso, the mass of the grounds and the brewed output need to be precisely measured. So, the office La Marzocco GS3 has been transformed into a closed-loop espresso machine with a Particle Photon and an Acaia Lunar waterproof scale at its heart.
Continue reading “Will Hack For Espresso” →
There’s an old saying, that you should do everything at least twice. Once to learn how to do it, and then a second time to do it right. Perhaps [Zweben] would agree, since he wasn’t satisfied with his first Neopixel clock and proceeded to build another one. One lesson learned: soldering 180 tiny solder joints isn’t much fun. This time, [Zweben] set out to make a printed circuit board and redesign the clock to make it easier to assemble.
The clock uses multiple copies of a single circuit board. The board holds Neopixel strips in a 7-segment arrangement. Each board can also hold all of the electronics needed to drive the clock. Only the first board gets the microcontroller and other circuits.
Continue reading “Color Changing Clock Uses PCB Digits” →
There’s a lot more to learning how to play the guitar than just playing the right notes at the right time and in the right order. To produce any sound at all requires learning how to do completely different things with your hands simultaneously, unless maybe you’re a direct descendant of Eddie Van Halen and thus born to do hammer ons. There’s a bunch of other stuff that comes with the territory, like stringing the thing, tuning it, and storing it properly, all of which can be frustrating and discouraging to new players. Add in the calluses, and it’s no wonder people like Guitar Hero so much.
[Jake] and [Jonah] have found a way to bridge the gap between pushing candy colored buttons and developing fireproof calluses and enough grip strength to crush a tin can. For their final project in [Bruce Land]’s embedded microcontroller design class, they made a guitar video game and a controller that’s much closer to the experience of actually playing a guitar. Whether you’re learning to play for real or just want to have fun, the game is a good introduction to the coordination required to make more than just noise.
Continue reading “Guitar Game Plays With Enhanced Realism” →
The future of humans is on Mars. Between SpaceX, Boeing, NASA, and every other national space program, we’re going to Mars. With this comes a problem: flying to Mars is relatively easy, but landing a large payload on the surface of another planet is orders of magnitude more difficult. Mars, in particular, is tricky: it has just enough atmosphere that you need to design around it, but not enough where we can use only parachutes to bring several tons down to the surface. On top of this, we’ll need to land our habitats and Tesla Roadsters inside a very small landing ellipse. Landing on Mars is hard and the brightest minds are working on it.
At this year’s Hackaday Superconference, we learned how hard landing on Mars is from Ara Kourchians (you may know him as [Arko]) and Steve Collins, engineers at the Jet Propulsion Laboratory in beautiful Pasadena. For the last few years, they’ve been working on COBALT, a technology demonstrator on how to use machine vision, fancy IMUs, and a host of sensors to land autonomously on alien worlds. You can check out the video of their Supercon talk below.
Continue reading “Extraterrestrial Autonomous Lander Systems To Touch Down On Mars” →
Previously, we discussed how to apply the most basic hypothesis test: the z-test. It requires a relatively large sample size, and might be appreciated less by hackers searching for truth on a tight budget of time and money.
As an alternative, we briefly mentioned the t-test. The basic procedure still applies: form hypotheses, sample data, check your assumptions, and perform the test. This time though, we’ll run the test with real data from IoT sensors, and programmatically rather than by hand.
The most important difference between the z-test and the t-test is that the t-test uses a different probability distribution. It is called the ‘t-distribution’, and is similar in principle to the normal distribution used by the z-test, but was developed by studying the properties of small sample sizes. The precise shape of the distribution depends on your sample size. Continue reading “Statistics And Hacking: A Stout Little Distribution” →
The 555 timer is one of that special club of integrated circuits that has achieved silicon immortality. Despite its advanced age and having had its functionality replicated and superceded in almost every way, it remains in production and is still extremely popular because it’s simply so useful. If you are of A Certain Age a 555 might well have been the first integrated circuit you touched, and in turn there is a very good chance that your project with it would have been a simple electric organ.
If you’d like to relive that project, perhaps [Alexander Ryzhkov] has the answer with his 555 piano. It’s an entry in our coin cell challenge, and thus uses a CMOS low voltage 555 rather than the power-hungry original, but it’s every bit the classic 555 oscillator with a switchable resistor ladder you know and love.
Physically the piano is a tiny PCB with surface-mount components and physical buttons rather than the stylus organs of yore, but as you can see in the video below the break it remains playable. We said it was tiny, but some might also use tinny.
Continue reading “The Tiniest Of 555 Pianos” →