Ever wanted your own gesture-controlled robot arm? [EbenKouao]’s DIY Arduino Robot Arm project covers all the bases involved, but even if a robot arm isn’t your jam, his project has plenty to learn from. Every part is carefully explained, complete with source code and a list of required hardware. This approach to documenting a project is great because it not only makes it easy to replicate the results, but it makes it simple to remix, modify, and reuse separate pieces as a reference for other work.
[EbenKouao] uses a 3D-printable robotic gripper, base, and arm design as the foundation of his build. Hobby servos and a single NEMA 17 stepper take care of the moving, and the wiring and motor driving is all carefully explained. Gesture control is done by wearing an articulated glove upon which is mounted flex sensors and MPU6050 accelerometers. These sensors detect the wearer’s movements and turn them into motion commands, which in turn get sent wirelessly from the glove to the robotic arm with HC-05 Bluetooth modules. We really dig [EbenKouao]’s idea of mounting the glove sensors to this slick 3D-printed articulated gauntlet frame, but using a regular glove would work, too. The latest version of the Arduino code can be found on the project’s GitHub repository.
Most of the parts can be 3D printed, how every part works together is carefully explained, and all of the hardware is easily sourced online, making this a very accessible project. Check out the full tutorial video and demonstration, embedded below.
Coroutines in Kotlin are a way to simplify writing asynchronous code, which is code that doesn’t necessarily execute in the order it is written. Coroutines are like light-weight threads that can be launched and managed easily, making it simpler to bridge together blocking and non-blocking code. (However, coroutines are not threads. They are more akin to suspending functions that play very well together.)
[Foalyy] found that the official Kotlin documentation on coroutines went into great detail on how coroutines function, but wanted a more bottom-up approach to understanding how they work and can be used. Luckily for anyone who thinks the same way, [Foalyy] wrote it all up and begins with a great recap of important elements, but if you prefer you can jump straight to the examples.
The Bosch BME680 is a super-capable environmental sensor, and [Random Nerd Tutorials] has married it to the ESP32 to create an air quality meter that serves as a great tutorial on not just getting the sensor up and running, but also in setting up a simple (and optional) web server to deliver the readings. It’s a great project that steps through everything from beginning to end, including how to install the necessary libraries and how to program the ESP32, so it’s the perfect weekend project for anyone who wants to learn.
The BME680 is a small part that communicates over SPI or I2C and combines gas, pressure, temperature, and humidity sensors. The gas sensor part detects a wide range of volatile organic compounds (VOCs) and contaminants, including carbon monoxide, which makes it a useful indoor air quality sensor. It provides only a relative measurement (lower resistance corresponds to lower air quality) so for best results it should be calibrated against a known source.
The tutorial uses the Arduino IDE with an add-on to support the ESP32, and libraries from Adafruit. Unfamiliar with such things? The tutorial walks through the installation of both. There’s a good explanation of the source code, and guidance on entering setup values (such as local air pressure, a function of sea level) for best results.
Everyone learns differently, but cognitive research shows that you tend to remember things better if you use spaced repetition. That is, you learn something, then after a period, you are tested. If you still remember, you get tested again later with a longer interval between tests. If you get it wrong, you get tested earlier. That’s the idea behind [Andy Matuschak ‘s]and [Michael Nielsen’s] quantum computing tutorial. You answer questions embedded in the text. You answer to yourself, so there’s no scoring. However, once you click to reveal the answer, you report if you got the answer correct or not, and the system schedules you for retest based on your report.
Does it work? We don’t know, but we have heard that spaced repetition is good for learning languages, among other things. We suspect that like most learning methods, it works better for some people than others.
The humble automotive alternator hides an interesting secret. Known as the part that converts power from internal combustion into the electricity needed to run everything else, they can also themselves be used as an electric motor.
These devices almost always take the form of a 3-phase alternator with the magnetic component supplied by an electromagnet on the rotor, and come with a rectifier and regulator pack to convert the higher AC voltage to 12V for the car electrical systems. Internally they have three connections to the stator coils which appear to be universally wired in a delta configuration, and a pair of connections to a set of brushes supplying the rotor coils through a set of slip rings. They have a surprisingly high capacity, and estimates put their capabilities as motors in the several horsepower. Best of all they are readily available second-hand and also surprisingly cheap, the Ford Focus unit shown here came from an eBay car breaker and cost only £15 (about $20).
We already hear you shouting “Why?!” at your magical internet device as you read this. Let’s jump into that.
For years we’ve seen a trickle of really interesting home automation projects that use the Node-RED package. Each time, the hackers behind these projects have raved about Node-RED and now I’ve joined those ranks as well.
You can get this up and running in less than an hour and I’m going to tackle that as well as examples for playing with MQTT, setting up a web GUI, and writing to log files. To make Node-RED persistent on your network you need a server, but it’s lean enough to run from a Raspberry Pi without issue, and it’s even installed by default in BeagleBone distributions. Code for all examples in this guide can be found in the tutorial repository. Let’s dive in!
They say that in order to understand recursion, you must first understand recursion. Once you master that concept, you might decide that it’s time to write your own compiler that can compile itself as a fun side project. According to [Warren] aka [DoctorWkt], who documented every step of writing this C compiler from scratch, a true compiler will be able to do that.
Some of the goals for the project included self-compiling, focusing on a real hardware platform, practicality, and simplicity. [Warren] outlines a lot of the theory of compilers as well, including all the lexical, grammar, and semantic analysis and then the final translation into assembly language, but really focuses on making this compiler one for practical use rather than just a theoretical implementation. He focuses on Intel x86-64 and 32-bit ARM platforms too, which are widely available.
This project is a long read and very thoroughly documented at around 100,000 words, so if you’ve ever been interested in compilers this is a great place to start. There are a lot of other great compiler tools floating around too, like the Compiler Explorer which shows you generated code as you write in a higher level language.