When we see RGB LEDs used in a project, they’re often used more for aesthetic purposes than as a practical source of light. It’s an easy way to throw some color around, but certainly not the sort of thing you’d try to light up anything larger than a desk with. Apparently nobody explained the rules to [Brian Harms] before he built Light[s]well.
Believe it or not, this supersized light installation doesn’t use any exotic hardware you aren’t already familiar with. Fundamentally, what we’re looking at is a WiFi enabled Arduino MKR1000 driving strips of NeoPixel LEDs. It’s just on a far larger scale than we’re used to, with a massive 4 x 8 aluminum extrusion frame suspended over the living room.
Onto that frame, [Brian] has mounted an undulating diffuser made of 74 pieces of laser-cut cardstock. Invoking ideas of waves or clouds, the light looks like its of natural or even biological origin while at the same time having a distinctively otherworldly quality to it.
The effect is even more pronounced when the RGB LEDs kick in, thanks to the smooth transitions between colors. In the video after the break, you can see Light[s]well work its way from bright white to an animated rainbow. As an added touch, he added Alexa voice control through Arduino’s IoT Cloud service.
While LED home lighting is increasingly becoming the norm, projects like Light[s]well remind us that we aren’t really embracing the possibilities offered by the technology. The industry has tried so hard to make LEDs fit into the traditional role of incandescent bulbs, but perhaps its time to rethink things.
Continue reading “Voice Controlled RGB LEDs Go Big”
A question: if you’re controlling the classic video game Street Fighter with gestures, aren’t you just, you know, street fighting?
That’s a question [Charlie Gerard] is going to have to tackle should her AI gesture-recognition controller experiments take off. [Charlie] put together the game controller to learn more about the dark arts of machine learning in a fun and engaging way.
The controller consists of a battery-powered Arduino MKR1000 with WiFi and an MPU6050 accelerometer. Held in the hand, the controller streams accelerometer data to an external PC, capturing the characteristics of the motion. [Charlie] trained three different moves – a punch, an uppercut, and the dreaded Hadouken – and captured hundreds of examples of each. The raw data was massaged, converted to Tensors, and used to train a model for the three moves. Initial tests seem to work well. [Charlie] also made an online version that captures motion from your smartphone. The demo is explained in the video below; sadly, we couldn’t get more than three Hadoukens in before crashing it.
With most machine learning project seeming to concentrate on telling cats from dogs, this is a refreshing change. We’re seeing lots of offbeat machine learning projects these days, from cryptocurrency wallet attacks to a semi-creepy workout-monitoring gym camera.
Continue reading “Arduino, Accelerometer, And TensorFlow Make You A Real-World Street Fighter”
For an electronics person, building the mechanics of a robot — especially a robust robot — can be somewhat daunting. [Jithin] started with an off-the-shelf 4 wheel drive chassis to build an off-road Arduino robot he calls the Badland Brawler. The kit was a bit over $100, but as you can see in the video below, it is pretty substantial, with an enclosed frame and large mud tires.
The remaining parts include an Arduino, a battery, and a motor driver IC. The Arduino is one with WiFi (an MKR 1000, in fact) and there’s a phone app for controlling the robot.
Honestly, once you have the chassis taken care of, the rest is pretty easy. Of course, the phone app is a bit more effort, but you could replace it in a number of ways. Blynk, comes to mind, for example.
The motor drivers are easy to figure out. This would be a great platform for some sensors to allow for more autonomy. We liked how the frame had mount points for a lot of different boards and sensors and could hold everything, for the most part, inside. That’s probably a good idea for a robot which will be traversing rugged terrain.
If you do decide to roll your own app with Blynk, we’ve done it with a very different kind of robot. Four-wheel drive robots don’t have to be big, as we’ve seen in the past.
Continue reading “Badland Brawler Lets Arduino Tackle Terrain”
Watching Tony Stark wave his hands to manipulate projected constructs is an ever-approaching reality — at least in terms of gesture-tracking. Lift — a prototype built by a team from UC Irvine and FX Palo Alto Laboratory — is able to track up to ten fingers with 1.7 mm accuracy!
Lift’s gesture-tracking is achieved by using a DLP projector, two Arduino MKR1000s, and a light sensor for each digit. Lift’s design allows it to work on virtually any flat surface; the projected image acts as a grid and work area for the user. As their fingers move across the projected surface, the light sensors feed the information from the image to the Arduinos, which infers the location of each finger and translate it into a digital workspace. Sensors may also be mounted on other objects to add functionality.
So far, the team has used Lift as an input device for drawing, as well as using it to feign gesture controls on a standard laptop screen. The next step would be two or more projectors which would allow Lift to function fully and efficiently in three dimensions and directly interacting with projected media content. Can it also operate wirelessly? Yes. Yes, it can.
While we don’t have Tony Stark’s hologram workstation quite yet, we can still play Tetris, fly drones, and mess around with surgical robots.
If you are a regular Hackaday reader, you’ve probably seen plenty of ESP8266 projects. After all, the inexpensive device is a workhorse for putting a project on WiFi, and it works well. There is a processor onboard, but, most often, the onboard CPU runs a stock firmware that exposes an AT command set or Lua or even BASIC. That means most projects have a separate CPU and that CPU is often–surprise–an Arduino.
It isn’t a big leap of logic to imagine an Arduino with an integrated WiFi subsystem. That’s the idea behind the MKR1000. But the real question you have to ask is: is it better to use an integrated component or just put an Arduino and ESP8266 together?
[Andreas Spiess] not only asked the question, but he answered it in a YouTube video (see below). He examines several factors on the MKR1000, the Arduino Due and Uno, and several other common boards. The examination covers performance, features, and power consumption.
Continue reading “ESP8266 Or MKR1000?”
[TVMiller] has a bone to pick with you if you let your car idle while you chat or text on your phone. He doesn’t like it, and he wants to break you of this wasteful habit – thus the idle-deterrence system he built that he seems to want on every car dashboard.
In the video below, the target of his efforts is clear – those who start the car then spend time updating Twitter or Instagram. His alarm is just an Arduino Nano that starts a timer when the car is started. Color-coded LEDs mark the time, and when the light goes red, an annoying beep starts to remind you to get on with the business of driving. The device also includes an accelerometer that resets the timer when the vehicle is in motion; the two-minute timeout should keep even the longest stop light from triggering the alarm.
[TVMiller] plans an amped-up version of the device built around an MKR1000 that will dump idle to moving ratios and other stats to the cloud. That’s a little too Big Brother for our tastes, but we can see his point about how wasteful just a few minutes of idling can be when spread over a huge population of vehicles. This hack might make a nice personal reminder to correct wasteful behavior. It could even be rolled into something that reads the acceleration and throttle position directly from the OBD port, like this Internet of Cars hack we featured a while back.
Continue reading “Car Idle Alarm Helps You Stop Wasting Gas While Tweeting”