In a world where smartphones have commoditized precision MEMS Sensors, the stage is set to reimagine clusters of these sensors as something totally different. That’s exactly what [chronopoulos] did, taking four proximity sensors and turning them into a custom gesture input sensor for sound generation. The result is Quadrant, a repurposable human-interface device that proves to be well-posed at detecting hand gestures and turning them into music.
At its core, Quadrant is a human interface device built around an STM32F0 and four VL6180X time-of-flight proximity sensors. The idea is to stream the measured distance data over as fast as possible from the device side and then transform it into musical interactions on the PC side. Computing distance takes some time, though, so [chronopoulos] does a pipelined read of the array to stream the data into the PC over USB at a respectable 30 Hz.
With the data collected on the PC side, there’s a spread of interactions that are possible. Want a laser harp? No problem, as [chronopoulos] shows how you can “pluck” the virtual strings. How about an orientation sensor? Simply spread your hand over the array and change the angle. Finally, four sensors will also let you detect sweeping gestures that pass over the array, like the swoosh of your hand from one side to the other. To get a sense of these interactions, jump to the video demos at the 2:15 mark after the break.
If you’re curious to dig into the project’s inner workings, [chronopoulos] has kindly put the firmware, schematics, and layout files on Github with a generous MIT License. He’s even released a companion paper [PDF] that details the math behind detecting these gestures. And finally, if you just want to cut to the chase and make music of your own, you can actually snag this one on Tindie too.
MEMs sensors are living a great second life outside our phones these days, and this project is another testament to the richness they offer for new project ideas. For more MEMs-sensor-based projects, have a look at this self-balancing robot and magic wand.
[Justin Lam] created a wonderfully-detailed writeup of his Smart Sourdough Lid project, which was created out of a desire to get better data on the progress and health of his sourdough starters, and to do so more efficiently. The result is a tidy, one-piece lid that constantly measures temperature, humidity, and height of the starter in the jar. Data is sent wirelessly for analysis, but there is also a handy OLED display on the top of the lid that shows immediately useful data like how much the starter has peaked, and how much time has passed since it did so.
We really like how focused the design is, and the level of detail [Justin] goes into to explain his design decisions and describe how well they worked out. This isn’t [Justin]’s first kick at the can when it comes to getting data on his sourdough, after all. We remember his earlier work using computer vision to analyze sourdough starters, and he used what he learned to inform this new design; the smart lid is easier to use and handles data much more efficiently.
The project’s GitHub repository has all the information needed to build your own. The lid is ESP8266-based and integrates a VL6180X time-of-flight (ToF) distance sensor, DHT22 to sense temperature and humidity, and a small SSD1306 OLED display for data. A small custom PCB keeps the modules tidy, and a 3D-printed custom enclosure makes it one tidy package.
[Justin] also analyzes the results he obtained and talks about what they mean in the last part of his writeup, so if you’re into baking and interested in his findings, be sure to give that a look.
A lighthouse beams light out to make itself and its shoreline visible. [Daniel’s] lighthouse has the opposite function, using lasers to map out the area around itself. Using an Arduino and a ToF sensor, the concept is relatively simple. However, connecting to something that rotates 360 degrees is always a challenge.
The lighthouse is inexpensive — about $40 — and small. Small enough, in fact, to mount on top of a robot, which would give you great situational awareness on a robot big enough to support it. You can see the device in action in the video below. Continue reading “Lidar House Looks Good, Looks All Around”→
Towering behemoths are prowling the docks of Auckland, New Zealand, in a neverending shuffle of shipping containers, stacking and unstacking them like so many out-sized LEGO bricks. And they’re doing it all without human guidance.
It’s hard to overstate the impact containerized cargo has had on the modern world. The ability to load and unload ships laden with containers of standardized sizes rapidly with cranes, and then being able to plunk those boxes down onto a truck chassis or railcar carrier for land transportation has been a boon to the world’s economy, and it’s one of the main reasons we can order electronic doo-dads from China and have them show up at our doors essentially for free. At least eventually.
As with anything, solving one problem often creates other problems, and containerization is no different. The advantages of being able to load and unload one container rather than separately handling the dozen or more pallets that can fit inside it are obvious. But what then does one do with a dozen enormous containers? Or hundreds of them?
That’s where these giant self-driving cranes come in, and as we’ll see in this installment of “Automate the Freight”, these autonomous stevedores are helping ports milk as much value as possible out of containerization.
Sometimes the best you can say about a project is, “Nice start.” That’s the case for this as-yet awful DIY 3D scanner, which can serve both as a launching point for further development and a lesson in what not to do.
Don’t get us wrong, we have plenty of respect for [bitluni] and for the fact that he posts his failures as well as his successes, like composite video and AM radio signals from an ESP32. He used an ESP8266 in this project, which actually uses two different sensors: an ultrasonic transducer, and a small time-of-flight laser chip. Each was mounted to a two-axis scanner built from hobby servos and 3D-printed parts. The pitch and yaw axes move the sensors through a hemisphere gathering data, but unfortunately, the Wemos D1 Mini lacks the RAM to render the complete point cloud from the raw points. That’s farmed out to a WebGL page. Initial results with the ultrasonic sensor were not great, and the TOF sensor left everything to be desired too. But [bitluni] stuck with it, and got a few results that at least make it look like he’s heading in the right direction.
We expect he’ll get this sorted out and come back with some better results, but in the meantime, we applaud his willingness to post this so that we can all benefit from his pain. He might want to check out the results from this polished and pricey LIDAR scanner for inspiration.
[JRodrigo]’s xLIDAR project is one of those ideas that seemed so attractively workable that it went directly to a PCB prototype without doing much stopping along the way. The concept was to mount a trio of outward-facing VL53L0X distance sensors to a small PCB disk, and then turn that disk with a motor and belt while taking readings. As the sensors turn, their distance readings can be used to paint a picture of the immediate surroundings (at least within about 1 meter, which is the maximum range of the VL53L0X.)
The hardware is made to be accessible and has a strong element of “what you see is what you get.” The distance sensors are on small breakout boards, and the board turns the sensor disk via a DC motor and 3D printed belt drive. Even the method of encoding the disk’s movement and zero position has the same WYSIWYG straightforwardness: a spring contact and an interrupted bare copper trace on the bottom of the sensor disk acts as a physical switch. In fact, exposed copper traces in concentric circular patterns and spring pins taken from an SD card socket are what provide power and communications as the disk turns.
The prototype looks good and sounds like it should work, but how well does it hold up? We’ll find out once [JRodrigo] does some testing. Until then, the board designs are available on the project’s GitHub repository if anyone wants to take a shot at their own approach without starting from scratch.
We’re all slowly getting used to the idea of wearable technology, fabulous flops like the creepy Google Glass notwithstanding. But the big problem with tiny tech is in finding the real estate for user interfaces. Sure, we can make it tiny, but human fingers aren’t getting any smaller, and eyeballs can only resolve so much fine detail.
So how do we make wearables more usable? According to Carnegie-Mellon researcher [Chris Harrison], one way is to turn the wearer into the display and the input device (PDF link). More specifically, his LumiWatch projects a touch-responsive display onto the forearm of the wearer. The video below is pretty slick with some obvious CGI “artist’s rendition” displays up front. But even the somewhat limited displays shown later in the video are pretty impressive. The watch can claim up to 40-cm² of the user’s forearm for display, even at the shallow projection angle offered by a watch bezel only slightly above the arm — quite a feat given the irregular surface of the skin. It accomplishes this with a “pico-projector” consisting of red, blue, and green lasers and a pair of MEMS mirrors. The projector can adjust the linearity and brightness of the display to provide a consistent image across the uneven surface. An array of 10 time-of-flight sensors takes care of watching the display area for touch input gestures. It’s a fascinating project with a lot of potential, but we wonder how the variability of the human body might confound the display. Not to mention the need for short sleeves year round.