One of the companion technologies in the developing field of augmented reality is gesture tracking. It’s one thing to put someone in a virtual or augmented world, but without a natural way to interact inside of it the user experience is likely to be limited. Of course, gestures can be used to control things in the real world as well, and to that end [Sarah]’s latest project uses this interesting human interface device to control a drone.
The project uses a Leap Motion sensor to detect and gather the gesture data, and feeds all of that information into LabVIEW. A Parrot AR Drone was chosen for this project because of a robust API that works well with this particular software suite. It seems as though a lot of the grunt work of recognizing gestures and sending commands to the drone are taken care of behind-the-scenes in software, so if you’re looking to do this on your own there’s likely to be quite a bit more work involved. That being said, it’s no small feat to get this to work in the first place and the video below is worth a view.
To some, gestures might seem like a novelty technology with no real applications, but they do have real-world uses for people with disabilities or others with unusual workflow that require a hands-free approach. So far we’ve seen hand gesture technologies that drive cars, help people get around in the physical world, and even play tetris.
Continue reading “Drone Takes Off With a Flick of the Wrist”
An ultrasonic beacon is an inaudible sound with encoded data that can be used by a listening device to receive information on just about anything. Beacons can be used, for example, inside a shop to highlight a particular promotion or on a museum for guided tours where the ultrasonic beacons can encode the location. Or they can be used to track
people consumers. Imagine if Google find outs… oh, wait… they already did, some years ago. As with almost any technology, it can be used to ‘do no harm’ or to serve other purposes.
Researchers from the Technische Universitat Braunschweig in Germany presented a paper about Ultrasonic Side Channels on Mobile Devices and how can they be abused in a variety of scenarios , ranging from simple consumer tracking to deanonymization. These types of ultrasonic beacons work in the 18 kHz – 20 kHz range, which the human being doesn’t have the ability to hear, unless you are under twenty years old, due to presbycusis. Yes, presbycusis. This frequency range can played via almost any speaker and can be picked up easily by most mobile device microphones, so no special hardware is needed. Speakers and mics are almost ubiquitous nowadays, so there is a real appeal to the technology.
Continue reading “Ultrasonic Tracking Beacons Rising”
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 solemnly swear that you are up to no good, and you happen to spend most of your time in Manhattan below the mid-90s, then you will appreciate this Raspberry Pi-based Manhattan Marauder’s Map.
Not that a Harry Potter-themed map was necessarily [GawkyFuse]’s intention when creating this interesting build; it’s just that the old-time print of Manhattan — it shows Welfare Island in the East River, which was renamed Roosevelt Island in 1971 — lends a nice vintage feel to the build. Printed on plain paper, the map overlays a 64×32-LED matrix, which is driven by a matrix HAT riding atop the Pi 3.
[GawkyFuse] uses the OwnTracks app on his and his wife’s iPhone to report their locations back to CloudMQTT. The Pi subscribes to the broker and updates his location in red and her location in blue as they move about the city; a romantic touch is showing a single purple dot when they’re together. There’s no word on what’s displayed when either leaves the map area, but the 2048-pixel display offers a lot of possibilities.
We’ve seen a Weasley clock or two around these parts before, but strangely no Marauder’s Maps like this one. Although this Austrian tram-tracking map comes pretty close to [GawkyFuse]’s nice design.
If it’s been a few years since you’ve been to Disney World, you’re in for a surprise on your next visit. It seems the Happiest Place on Earth has become the Trackiest Place on Earth thanks to the Disney MagicBand, a multipurpose wristband that acts as your pass to all the Disney magic.
[Adam] recently returned from a Disney vacation and brought back his MagicBand, which quickly went under the knife for a peek at the magic inside. It turns out the technology is fairly mundane — a couple of flex PCBs with trace antennas and the usual trappings of an RFID transponder. But there’s also another antenna and a chip identified in a separate teardown as an NRF24LE1 2.4 GHz transceiver and microcontroller. The whole thing is powered by a coin cell, meaning the band isn’t just being interrogated by RFID – it’s actively transmitting and receiving.
What exactly it’s doing isn’t clear; Disney was characteristically cagey about specifics when [Adam] looked into the details, saying only that the bands “provide information that helps us improve the overall experience in our parks”. If you put aside the privacy concerns, it’s truly mind-boggling to think about the systems that must be in place to track thousands of these MagicBands around the enormous Disney property. And we can’t help but wonder if some of Disney R&D’s EM-Sense technology is at work in these wearables.
Thanks to [JohnU] for the tip.
With interest and accessibility to both wearable tech and virtual reality approaching an all-time high, three students from Cornell University — [Daryl Sew, Emma Wang, and Zachary Zimmerman] — seek to turn your body into the perfect controller.
That is the end goal, at least. Their prototype consists of three Kionix tri-axis accelerometer, gyroscope and magnetometer sensors (at the hand, elbow, and shoulder) to trace the arm’s movement. Relying on a PC to do most of the computational heavy lifting, a PIC32 in a t-shirt canister — hey, it’s a prototype! — receives data from the three joint positions, transmitting them to said PC via serial, which renders a useable 3D model in a virtual environment. After a brief calibration, the setup tracks the arm movement with only a little drift in readings over a few minutes.
Continue reading “Your Arm Is The Ideal Controller”
There aren’t too many sports named for the sound that is produced during the game. Even though it’s properly referred to as “table tennis” by serious practitioners, ping pong is probably the most obvious. To that end, [Nekojiru] built a ping pong ball juggling robot that used those very acoustics to pinpoint the location of the ball in relation to the robot. Not satisfied with his efforts there, he moved onto a visual solution and built a new juggling rig that uses computer vision instead of sound to keep a ping pong ball aloft.
The main controller is a Raspberry Pi 2 with a Pi camera module attached. After some mishaps with the planned IR vision system, [Nekojiru] decided to use green light to illuminate the ball. He notes that OpenCV probably wouldn’t have worked for him because it’s not fast enough for the 90 fps that’s required to bounce the ping pong ball. After looking at the incoming data from this system, an algorithm extracts 3D information about the ball and directs the paddle to strike the ball in a particular way.
If you’ve ever wanted to get into real-time object tracking, this is a great project to look over. The control system is well polished and the robot itself looks almost professionally made. Maybe it’s possible to build something similar to test [Nekojiru]’s hypothesis that OpenCV isn’t fast enough for this. If you want to get started in that realm of object tracking, there are some great projects that make use of that piece of software as well.