Hackaday Prize Entry: SNAP Is Almost Geordi La Forge’s Visor

Echolocation projects typically rely on inexpensive distance sensors and the human brain to do most of the processing. The team creating SNAP: Augmented Echolocation are using much stronger computational power to translate robotic vision into a 3D soundscape.

The SNAP team starts with an Intel RealSense R200. The first part of the processing happens here because it outputs a depth map which takes the heavy lifting out of robotic vision. From here, an AAEON Up board, packaged with the RealSense, takes the depth map and associates sound with the objects in the field of view.

Binaural sound generation is a feat in itself and works on the principle that our brains process incoming sound from both ears to understand where a sound originates. Our eyes do the same thing. We are bilateral creatures so using two ears or two eyes to understand our environment is already part of the human operating system.

In the video after the break, we see a demonstration where the wearer doesn’t need to move his head to realize what is happening in front of him. Instead of a single distance reading, where the wearer must systematically scan the area, the wearer simply has to be pointed the right way.

Another Assistive Technology entry used the traditional ultrasonic distance sensor instead of robotic vision. There is even a version out there for augmented humans with magnet implants covered in Cyberpunk Yourself called Bottlenose.

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Hackaday Prize Semifinalist: Superhero Powers

The inspiration for [K.C. Lee]’s project for The Hackaday Prize didn’t come from seeing a grave injustice or inhuman suffering. He was watching Daredevil on Netflix. A show about a blind guy who fights crime in his spare time. People don’t have superhuman senses, and radioactive material falling off a truck in New York City leads to Ninja Turtles, not superheros. Still, a crude form of echolocation is well within the reach of the a capable hacker and would be very useful for those who are legally blind.

[K.C.]’s idea for human echolocation is a small wearable with ultrasonic sensors, 6DOF IMUs, and audio and haptic feedback. With a bit of math and a lot of practice, it’s possible to walk down a hallway, avoid obstacles, and find your way around without sight.

Human echolocation is a real thing, and it’s great to see a device that makes this minor human superpower a little more accessible. [K.C.] says there are 40 million people world wide that could use a device like this, and for an idea that was inspired by a superhero on TV, it’s one of the more interesting inspirations for an entry to The Hackaday Prize.

 

The 2015 Hackaday Prize is sponsored by:

Echolocation pinpoints where a gunshot came from

echolocating-gunshots

[Kripthor] suspected that hunters were getting too near his house. When thinking of a way to quantify this belief he set out to build a triangulation system based on the sound of gunshots. The theory behind it is acoustic location, which is a specialized type echolocation.

The most common example of echolocation is in Bats, who emit ultrasonic noise and listen for its return (echo) to judge the location of objects. [Kripthor] doesn’t need to generate the sound himself, he just needs to pick it up at different points. The time difference from the three samples can be used to triangulate coordinates as seen in the image above.

He first tried using a PC sound card to collect the samples. The stereo input only provides two channels so he tinkered around with a 555-based multiplexing circuit to sample from three. The circuit noise created was just too great so he transitioned to using an Arduino. The ADC samples from each microphone via an NPN transistor which is used as a simple amplifier.

This brings to mind a homebrew sonar hack from way back.

Build a simple bat detector


[Tony Messina] had been fascinated with bat’s echolocation since he was a kid. After he retired, he decided to act on this fascination and built a simple bat detector.

The simple bat detector uses frequency division to lower the bat’s chirping to a frequency we can hear. For example, if a bat is calling at 91kHz the system will divide it by 16 and put out 5.7kHz. The system is digital, so all amplitude is lost. You’ll just hear clicks like a Geiger counter. Being digital has its advantages though. Unlike similar analog devices that have to be tuned to a small frequency range, the simple bat detector can detect a much wider window.

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