After booting up his RetroPie system, [jfrmilner] had the distinct feeling that something was off. Realizing that the modern Xbox 360 controller didn’t fit right when reliving the games of his youth, he rounded up all his old controllers to make sure he always had the right gamepad for the game.
Wanting to keep the controllers unmodified — so they could still be used on the original systems — he had to do a bit of reverse-engineering and source some controller sockets before building his controller hub. Using shift-in registers, shift-out registers, and some multiplexers, he designed a large circuit selector — which acts as a shield for an Arduino Micro — so all the controllers remain connected. A potentiometer allows him to select the desired controller and a few arcade buttons which access RetroPie shortcuts really round out the hub. Check out the demo after the break!
[jfrmilner] kept the controllers relevant to the games he would be playing, but we hope there’s some room to include a controller in rug format in his build. Of course, there’s always the option of Jerry-rigging old systems to use your preferred retro gamepad.
Starting a new project is always a fun yet effective way to hone your skills while exploring circuitry and programming. To help improve his engineering chops, Joop Brokking recently bought an inexpensive oscilloscope (a device for visualizing voltage over time in an x-y graph) and connected it to an Arduino Uno. He then shared his findings in a detailed tutorial on YouTube.
In the video below, Brokking is using a Hantek 6022BE 20MHz dual-channel oscilloscope and provides three examples to better understand what can go wrong when building a simple Arduino setup.
Starting a new project is always a fun yet effective way to hone your skills while exploring circuitry and programming. To help improve his engineering chops, Joop Brokking recently bought an inexpensive oscilloscope (a device for visualizing voltage over time in an x-y graph) and connected it to an Arduino Uno. He then shared his findings in a detailed tutorial on YouTube.
In the video below, Brokking is using a Hantek 6022BE 20MHz dual-channel oscilloscope and provides three examples to better understand what can go wrong when building a simple Arduino setup.
Last year, we featured an awesome audiovisual project from ANGLE that applied videomapping techniques to their livesets. Now, the Florence-based duo is back with their latest A/V system, “Shining Back,” which was designed in collaboration with JoinT Studio’s Stefano Bonifazi.
Essentially, it’s a grid structure consisting of LED lights that pulse in a geometric matrix to the duo’s live rhythms. The installation runs on an Arduino Uno and uses Mad Mapper and Modul8 software.
The immersive atmosphere created by the music is emphasized by a new research in the visual realm. Taking an architectural form of a kaleidoscope the lighting visually weaves and refracts the music into a surreal yet symbiotic form.
Gyroscopes and accelerometers are the primary sensors at the heart of an IMU, also known as an internal measurement unit — an electronic sensor device that measures the orientation, gravitational forces and velocity of a multicopter, and help you keep it in the air using Arduino.
Two videos made by Joop Brokking, a Maker with passion for RC model ‘copters, clearly explain how to program your own IMU so that it can be used for self-balancing your drone without Kalman filters, libraries, or complex calculations.
Auto leveling a multicopter is pretty challenging. It means that when you release the pitch and roll controls on your transmitter the multicopter levels itself. To get this to work the flight controller of the multicopter needs to know exactly which way is down. Like a spirit level that is on top of the multicopter for the pitch and roll axis.
Very often people ask me how to make an auto level feature for their multicopter. The answer to a question like this is pretty involved and cannot be explained in one email. And that is why I made this video series.
At Arduino Day, I talked about a project I and my collaborators have been working on to bring machine learning to the maker community. Machine learning is a technique for teaching software to recognize patterns using data, e.g. for recognizing spam emails or recommending related products. Our ESP (Example-based Sensor Predictions) software recognizes patterns in real-time sensor data, like gestures made with an accelerometer or sounds recorded by a microphone. The machine learning algorithms that power this pattern recognition are specified in Arduino-like code, while the recording and tuning of example sensor data is done in an interactive graphical interface. We’re working on building up a library of code examples for different applications so that Arduino users can easily apply machine learning to a broad range of problems.
Our project is part of a broader wave of projects aimed at helping electronics hobbyists make more sophisticated use of sensors in their interactive projects. Also building on the GRT is ml-lib, a machine learning toolkit for Max and Pure Data. Another project in a similar vein is the Wekinator, which is featured in a free online course on machine learning for musicians and artists. Rebecca Fiebrink, the creator of Wekinator, recently participated in a panel on machine learning in the arts and taught a workshop (with Phoenix Perry) at Resonate ’16. For non-real time applications, many people use scikit-learn, a set of Python tools. There’s also a wide range of related research from the academic community, which we survey on our project wiki.
For a high-level overview, check out this visual introduction to machine learning. For a thorough introduction, there are courses on machine learning from coursera and from udacity, among others. If you’re interested in a more arts- and design-focused approach, check out alt-AI, happening in NYC next month.
If you’d like to start experimenting with machine learning and sensors, an excellent place to get started is the built-in accelerometer and gyroscope on the Arduino or Genuino 101. With our ESP system, you can use these sensors to detect gestures and incorporate them into your interactive projects!
Massimo Banzi is among the judges on “America’s Greatest Makers” a reality competition from Mark Burnett (the reality-TV king behind “Survivor,” “The Apprentice,” and “The Voice”) in partnership with Intel which debuted last week on TBS.
In a first of its kind competition, the tv show takes 24 teams of makers from across US and puts them in head-to-head challenges to invent disruptive projects and win $1 million. The team are composed by unique people from 15 years old to 59 with ideas going to inspire a whole new audience of potential makers.
In the first two episodes, each team pitched their device idea to the judging panel composed by Intel CEO Brian Krzanich; business and financial expert Carol Roth; comedian, serial entrepreneur and co-host of truTV’s Hack My Life Kevin Pereira; and one of the celebrity guests.
At the end of April during 4th episode guest judge Massimo Banzi joins the panel as the remaining makers compete in the “Make or Break” rounds for $100,000 and a spot in the million dollar finale. If you are not in the USA, watch the episode at this link after April 27th.
In the meanwhile you can also watch a beginner maker project to learn how to do obstacle avoidance using Arduino 101. Cara Santa Maria is the trainer who’s going to guide you into the tutorial about this really important topic for projects involving moving objects like robots and drones:
Is there a cool Internet of Things idea that you’ve wanted to try out with your Arduino, but just haven’t had time for? Building a network that integrates multiple sensors and boards into one cohesive application can be time-consuming and difficult. To make it a bit easier, Temboo just introduced new Machine-to-Machine programming that lets you connect Arduino and Genuino boards running locally in a multi-device network to the Internet. Now, you can bring all the power and flexibility of Internet connectivity to Arduino applications without giving up the benefits of using low power, local devices.
Our friends at Temboo now support three M2M communication protocols for Arduino boards: MQTT, CoAP, and HTTP. You can choose which to use based on the needs of your application and, once you’ve made your choice, automatically generate all the code you need to connect your Arduinos to any web service. You can also save the network configurations that you specify, making it easy to add and subtract devices or update their behavior remotely.
With Temboo M2M, you can program flexible distributed device applications in minutes. From monitoring air quality and noise levels in cities to controlling water usage in agricultural settings, networked sensors and devices enable all sorts of powerful IoT applications. You can see it all in action in the video below, which shows how they built an M2M network that monitors and controls different machines working together on a production line.
Rebel Geeks is a seven-part series on Al Jazeera English channel, featuring profiles of people around the world challenging power structures and offering a different vision of our technological future.
During Makers Faire in Shenzhen, in southeastern China, the authors of the series met Massimo Banzi and produced‘ Meet Your Maker’, a video interview about Arduino and how thousands of people are adopting it to build everything from 3D printers to drones, smart home devices to robotics.
‘Meet Your Maker’ can be seen on Al Jazeera English from November 16 at 22.30GMT.
Planet Arduino is, or at the moment is wishing to become, an aggregation of public weblogs from around the world written by people who develop, play, think on Arduino platform and his son. The opinions expressed in those weblogs and hence this aggregation are those of the original authors. Entries on this page are owned by their authors. We do not edit, endorse or vouch for the contents of individual posts. For more information about Arduino please visit www.arduino.cc
You are currently browsing the archives for the video category.