Professor [Bruce Land] teaches a microcontroller class at Cornell University, and it seems like this year’s theme was selfie-taking-robots.
First up is a clever mix of technology by [Han, Bihan and Chuan]. What happens when you take an iPhone, three microphones and a microcontroller? The ultimate device in selfie-taking-technology, that’s what — Clap-on! The iPhone is mounted on a few servo motors which allows the bot to direct the camera towards, you guessed it, a clapping noise. On the second clap, the phone takes your picture. Cute.
Next up is a bit more sophisticated — a facial recognition selfie-bot. This little robot can be programmed to track faces and take pictures of you and your friends when your arm is just not long enough. Not only that, you can set all kinds of parameters so you get the perfect picture. It uses OpenCV to crunch the raw data and outputs commands to an ATmega1284 which controls the servo motors that direct the camera. This project was by [Michael and Jennifer] — two fourth year students at Cornell.
Continue reading “Selfie-Bots Will Take Your Best Shots For You”
Pinball machines are fascinating pieces of mechanical and electrical engineering, and now [Yair Moshe] and his students at the Israel Institute of Technology has taken the classic game one step further. Using computer vision and a projector, this group of engineers has created an augmented reality pinball game that takes pinball to a whole new level.
Once the laptop, webcam, and projector are set up, a course is drawn on a whiteboard which the computer “sees” to determine the rules of the game. Any course you can imagine can be drawn on the whiteboard too, with an interesting set of rules that no regular pinball game could take advantage of. Most notably, the ball can change size when it hits certain types of objects, which makes for a very interesting and unconventional style of play.
The player uses their hands to control the flippers as well, but not with buttons. The computer watches the position of the player’s hands and flips the flippers when it sees a hand in the right position. [Yair] and his students recently showed this project off at DLD Tel Aviv and even got [Shimon Perez], former President of Israel, to play some pinball at the conference!
[Eric] just sent in this awesome Kinect hack that he and a few friends worked on. Playing Super Smash Bros with a Kinect.
The system makes use of two Kinects, and three PCs. The first Kinect records each individual players moves, while the second Kinect watches both players “fight” each other. The first PC runs an Nintendo 64 emulator to play the game.
The second PC runs a camera with OpenCV to add another cool but perhaps unnecessary feature, you see, even the character selection is a physical process, adding to the idea of playing the entire game with your body. A glass table allows players to set their 3D printed token onto the glass, effectively placing it on the character they would like to use.
And when the match ends, a windshield wiper knocks off the losing player’s token from the table.
The third PC is responsible for running both Kinects, which then has to send the resulting commands back to first PC over a TCP connection for input into the game.
They introduced it to the public at MHacks Fall 2014, a hacking competition sponsored by Dell and Intel. Video Below.
Continue reading “Super Smash Bros Gets a Revamp with the Microsoft Kinect”
By now you’ve seen almost anything Tweet. But have you seen the (French) twittering chicken coop? (Google translate link) [Hugo] had kept two chickens as part of a household-waste reduction campaign, and then afterward started work.
Even if you don’t read French, the chickens’ twitter feed basically tells the story.
The setup can take IR photographs of sleeping chickens and notify [Hugo] when it’s time to collect the eggs. Naturally, an abundance of other sensors are available. The coop can tweet based on ambient temperature, nest temperature, light level, motion sensor status, or the amount of remaining chicken feed. You can easily follow whether the two fowl are in the coop or out in the yard. It’s like Big Brother, only for birds.
The application is, frankly, ridiculous. But if you’re into home (or coop) automation, there’s a lot to be learned and the project is very well documented. [Hugo] used OpenCV for visual egg detection, and custom Python code to slightly randomize the tweets’ text. All of these details are up on his Github account.
And if you just can’t get enough chicken-coop hacks, be sure to check out this mobile chicken coop, this coop in the shape of a golden spiral, or this Bluetooth-enabled, talking chicken coop, among others. You’d think our name was Coop-a-Day.
Even with visions of quadcopters buzzing around metropolitan areas delivering everything from pizzas to toilet paper fresh in the minds of tech blogospherites, There’s been a comparatively small amount of research into how to support squadrons of quadcopters and other unmanned aerial vehicles. The most likely cause of this is the FAA’s reactionary position towards UAVs. Good thing [Giovanni] is performing all his research for autonomous recharging and docking for multirotors in Australia, then.
The biggest obstacle of autonomous charging of a quadcopter is landing a quad exactly where the charging station is; run of the mill GPS units only have a resolution of about half a meter, and using a GPS solution would require putting GPS on the charging station as well. The solution comes from powerful ARM single board computers – in this case, an Odroid u3 – along with a USB webcam, OpenCV and a Pixhawk autopilot.
Right now [Giovanni] is still working out the kinks on his software system, but he has all the parts and the right tools to get this project up in the air, down, and back up again.
The project featured in this post is a semifinalist in The Hackaday Prize.
[Bharath] recently uploaded the source code for an OpenCV based pattern recognition platform that can be used for Augmented Reality, or even robots. It was built with C++ and utilized the OpenCV library to translate marker notations within a single frame.
The program started out by focusing in on one object at a time. This method was chosen to eliminate the creation of additional arrays that contained information of all of the blobs inside the image; which could cause some problems.
Although this implementation did not track marker information through multiple frames, it did provide a nice foundation for integrating pattern recognition into computer systems. The tutorial was straightforward and easy to ready. The entire program and source code can be found on Github which comes with a ZERO license so that anyone can use it. A video of the program comes up after the break:
Continue reading “Open Source Marker Recognition for Augmented Reality”
[Dr. Fortin] teaches physics at a French High School, and to get his students interested in the natural world around them, he built a geomagnetic observatory, able to tell his students if they have a chance at seeing an aurora, or if a large truck just drove by.
We’ve seen this sort of device before, and the basic construction is extremely similar – a laser shines on a mirror attached to magnets. When a change occurs in the local magnetic field, the mirror rotates slightly and the laser beam is deflected. Older versions have used photoresistors, but [the doctor] is shining his laser on a piece of paper and logging everything with a webcam and a bit of OpenCV.
The design is a huge improvement over earlier DIY attempts at measuring the local magnetic field, if only because the baseline between the webcam and mirror are so long. When set up in his house, the magnetometer can detect cars parked in front of his building, but the data he’s collecting (French, but it’s just a bunch of graphs) is comparable to the official Russian magnetic field data.