Researchers from Denmark’s Aarhus University have developed a method for autonomous drone scanning and measurement of terrains, allowing drones to independently navigate themselves over excavation grounds. The only human input is a starting location and the desired cliff face for scanning.
For researchers studying quarries, capturing data about gravel, walls, and other natural and man-made formations is important for understanding the properties of the terrain. Controlling the drones can be expensive though, since there’s considerable skill involved in manually flying the drone and keeping its camera steady and perpendicular to the wall it is capturing.
The process designed is a Gaussian model that predicts the wind encountered near the wall, estimating the strength based on the inputs it receives as it moves. It uses both nonlinear model predictive control (NMPC) and a PID controller in its feedback control system, which calculate the values to send to the drone’s motor controller. A long short-term memory (LSTM) model is used for calculating the predictions. It’s been successfully tested in a chalk quarry in Denmark and will continue to be tested as its algorithms are improved.
Getting a drone to hover and move between GPS waypoints is easy enough, but once they need to maneuver around obstacles it starts getting tricky. Research like this will be invaluable for developing systems that help drones navigate in areas where their human operators can’t reach.
[Thanks to Qes for the tip!]
Right off the bat, we’ll say that this video showing a laser beam stopping in mid-air is nothing but a camera trick. But it’s the trick that’s the hack, and you’ve got to admit that it looks really cool.
It starts with the [Tom Scott] video, the first one after the break. [Tom] is great at presenting fascinating topics in a polished and engaging way, and he certainly does that here. In a darkened room, a begoggled [Tom] poses with what appears to be a slow-moving beam of light, similar to a million sci-fi movies where laser weapons always seem to disregard the laws of physics. He even manages to pull a [Kylo Ren] on the slo-mo photons with a “Force Stop” as well as a slightly awkward Matrix-style bullet-time shot. It’s entertaining stuff, and the effect is all courtesy of the rolling shutter effect. The laser beam is rapidly modulated in sync with the camera’s shutter, and with the camera turned 90 degrees, the effect is to slow down or even stop the beam.
The tricky part of the hack is the laser stuff, which is the handiwork of [Seb Lee-Delisle]. The second video below goes into detail on his end of the effect. We’ve seen [Seb]’s work before, with a giant laser Asteroids game and a trick NES laser blaster that rivals this effect.
Continue reading “Camera And Code Team Up To Make Impossible Hovering Laser Effect”
[QLRO] wanted a 3D scanner, but didn’t like any of the existing designs. Some were too complex. Some were simple but required you to do things by hand. That led to him designing his own that he calls AAScan. You can see the thing operating in the video below.
In general, you can move the camera around the object or you can move the object around while the camera stays fixed. This design chooses the latter. You’ll need a stepper motor with a driver board and an Arduino to make the turntable rotate. You also need a computer running Python and Meshroom. The phone also has to run Python and [QLRO] used QPython on an Android device.
Continue reading “3D Print Your 3D Scanner”
A digital camera has an array of sensors that captures light reflected or transmitted onto it. This build is something closer to a reverse camera – a single sensor that makes images on a matrix of LEDs. And we think it’s pretty neat.
We have to admit to being a little confused by [marciot]’s LED matrix scanner when we first stumbled upon it. From the video below we thought that the LEDs in the matrix were being used both to detect incident light and as a display. We’ve seen LEDs used as photodiodes before, so such a contraption could work, but that’s not what’s going on here. A phototransistor is wired to an Arduino Uno and positioned above a 32×32 RGB LED matrix. A scanning routine rasters over the LEDs in the matrix while the sensor watches, and then the program turns on the LEDs that the sensor saw during the scan. Positioned far above the matrix, a large disc of light results, making it look like the phototransistor is beaming light down onto the matrix. The effect is reinforced by placing something between the sensor and the matrix, which casts a virtual shadow. Used close to the LEDs the sensor acts more like a light pen.
It’s a cool effect and it looks like a fun project to throw together. Refresh time could perhaps be a bit snappier, though; maybe an ESP32 could help with that.
Continue reading “LED Matrix And A Phototransistor Make A Reverse Camera”
What’s the best way to image a room? A picture? Hah — don’t be so old-fashioned! You want a LIDAR rig to scan the space and reconstruct it as a 3D point map in your computer.
Hot on the heels of [Saulius Lukse]’s scanning thermometer, he’s replaced the thermal camera on their pan/tilt setup with a time-of-flight (TOF) camera — a Garmin LIDAR — capable of 500 samples per second and end up scanning their room in a mere fifteen minutes. Position data is combined with the ranging information to produce a point cloud using Python. Open that file in a 3D manipulation program and you’ll be treated to a sight like this:
Continue reading “Digitize Your Room With LIDAR”
Want to know which way to point your WiFi antenna to get the best signal? It’s a guessing game for most of us, but a quick build of a scanning WiFi antenna using mostly off-the-shelf components could point you in the right direction.
With saturation WiFi coverage in most places these days, optimizing your signal might seem like a pointless exercise. And indeed it seems [shawnhymel] built this more for fun than for practical reasons. Still, we can see applications where a scanning Yagi-Uda antenna would come in handy. The build started with a “WiFi divining rod” [shawnhymel] created from a simple homebrew Yagi-Uda and an ESP8266 to display the received signal strength indication (RSSI) from a specific access point. Tired of manually moving the popsicle stick and paperclip antenna, he built a two-axis scanner to swing the antenna through a complete hemisphere.
The RSSI for each point is recorded, and when the scan is complete, the antenna swings back to the strongest point. Given the antenna’s less-than-perfect directionality — [shawnhymel] traded narrow beam width for gain — we imagine the “strongest point” is somewhat subjective, but with a better antenna this could be a handy tool for site surveys, automated radio direction finding, or just mapping the RF environment of your neighborhood.
Yagi-Uda antennas and WiFi are no strangers to each other, whether it be a WiFi sniper rifle or another recycling bin Yagi. Of course this scanner isn’t limited to WiFi. Maybe scanning a lightweight Yagi for the 2-meter band would be a great way to lock onto the local Ham repeater.
Continue reading “Simple Scanner Finds The Best WiFi Signal”
The best thing about owning a 3D printer or CNC router may not just be what you can additively or subtractively create with it. With a little imagination you can turn your machine into a 3D scanner, and using capacitive sensors to image items turns out to be an interesting project.
[Nelson]’s scanner idea came from fiddling with some capacitive sensors at work, and with a high-resolution capacitance-to-digital sensor chip in hand, he set about building a scan head for his printer. In differential mode, the FDC2212 sensor chip uses an external LC tank circuit with two plain sensor plates set close to each other. The sensor plates form an air-dielectric variable capacitor, and the presence of an object can be detected with high sensitivity. [Nelson]’s custom sensor board and controller ride on a 3D-printed bracket and scan over the target on the printer bed. Initial results were fuzzy, but after compensating for room temperature variations and doing a little filtering on the raw data, the scans were… still pretty fuzzy. But there’s an image there, and it’s something to work with.
Need a slightly more approachable project to get your feet wet with capacitive sensors? Maybe you should use your phone’s touchscreen as a 2D-capacitive scanner.