Hackaday Podcast 003: Igloos, Lidar, And The Blinking LED Of RF Hacking

January 25, 2019 by Mike Szczys 8 Comments

It’s cold outside! So grab a copy of the Hackaday Podcast, and catch up on what you missed this week.

Highlights include a dip into audio processing with sox and FFMPEG, scripting for Gmail, weaving your own carbon fiber tubes, staring into the sharpest color CRT ever, and unlocking the secrets of cheap 433 MHz devices. Plus Elliot talks about his follies in building an igloo while Mike marvels at what’s coming out of passive RFID sensor research.

And what’s that strange noise at the end of the podcast?

Take a look at the links below if you want to follow along, and as always, tell us what you think about this episode in the comments!

Direct download (60 MB or so.)

Continue reading “Hackaday Podcast 003: Igloos, Lidar, And The Blinking LED Of RF Hacking” →

New Part Day: Small, Cheap, And Good LIDAR Modules

January 22, 2019 by Brian Benchoff 40 Comments

Fully autonomous cars might never pan out, but in the meantime we’re getting some really cool hardware designed for robotic taxicab prototypes. This is the Livox Mid-40 Lidar, a LIDAR module you can put on your car or drone. The best part? It only costs $600 USD.

The Livox Mid-40 and Mid-100 are two modules released by Livox, and the specs are impressive: the Mid-40 is able to scan 100,000 points per second at a detection range of 90 m with objects of 10% reflectivity. The Mid-40 sensor weighs 710 grams and comes in a package that is only 88 mm x 69 mm x 76 mm. The Mid-100 is basically the guts of three Mid-40 sensors stuffed into a larger enclosure, capable of 300,000 points per second, with a FOV of 98.4° by 38.4°.

The use case for these sensors is autonomous cars, (large) drones, search and rescue, and high-precision mapping. These units are a bit too large for a skateboard-sized DIY Robot Car, but a single Livox Mid-40 sensor, pointed downward on a reasonably sized drone could perform aerial mapping

There is one downside to the Livox Mid sensors — while you can buy them direct from the DJI web site, they’re not in production. These sensors are only, ‘Mass-Production ready’. This might be just Livox testing the market before ramping up production, a thinly-veiled press release, or something else entirely. That said, you can now buy a relatively cheap LIDAR module that’s actually really good.

Hackaday Links: January 20, 2019

January 20, 2019 by Brian Benchoff 18 Comments

Let’s say you’re an infosec company, and you want some free press. How would you do that? The answer is Fortnite. Yes, this is how you hack Fortnite. This is how to hack Fortnite. The phrase ‘how to hack Fortnite’ is a very popular search term, and simply by including that phrase into the opening paragraph of this post guarantees more views. This is how you SEO.

Lasers kill cameras. Someone at CES visited the AEye booth, snapped a picture of an autonomous car at AEye’s booth, and the LIDAR killed the sensor. Every subsequent picture had a purple spot in the same place. While we know lasers can kill camera sensors, and this is a great example of that, this does open the door to a few questions: if autonomous cars have LIDAR and are covered in cameras, what’s going to happen to the cameras in an autonomous car driving beside another autonomous car? Has anyone ever seen more than one Cruise or Waymo car in the same place at the same time? As an aside, AEye’s company website’s URL is aeye.ai, nearly beating penisland.net (they sell pens on Pen Island) as the worst company URL ever.

This is something I’ve been saying for years, but now there’s finally a study backing me up. Lego is a viable investment strategy. An economist at Russia’s Higher School of Economics published a study, collecting the initial sale price of Lego sets from 1987 to 2015. These were then compared to sales of full sets on the secondary market. Returns were anywhere between 10 and 20% per year, which is crazy. Smaller sets (up to about 100 pieces) had higher returns than larger sets. This goes against my previous belief that a Hogwarts Castle, Saturn V, and UCS Falcon-heavy portfolio would outperform a portfolio made of cheap Lego sets. However, this observation could be tied to the fact that smaller sets included minifig-only packaging, and we all know the Lego minifig market is a completely different ball of wax. The Darth Revan minifig, sold as an exclusive for $3.99 just a few years ago, now fetches $35 on Bricklink. Further study is needed, specifically to separate the minifig market from the complete set market, but the evidence is coming in: Lego is a viable investment strategy, even when you include the 1-2% yearly cost of storing the sets.

Relativity Space got a launchpad. Relativity Space is an aerospace startup that’s building a rocket capable of lobbing my car into Low Earth Orbit with a methalox engine. They’re doing it with 3D printing. [Bryce Salmi], one of the hardware engineers at Relativity Space, recently gave a talk at the Hackaday Superconference about printing an entire rocket. The design is ambitious, but if there’s one device that’s perfectly suited for 3D printing, it’s a rocket engine. There are a lot of nonmachinable tubes going everywhere in those things.

Fail Of The Week: How Not To Make A 3D Scanner

July 23, 2018 by Dan Maloney 12 Comments

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.

Continue reading “Fail Of The Week: How Not To Make A 3D Scanner” →

XLIDAR Is A Merry-Go-Round Of Time-Of-Flight Sensors

June 29, 2018 by Donald Papp 38 Comments

[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.

A LIDAR Scanner Build In Glorious Detail

June 29, 2018 by Lewin Day 15 Comments

LIDAR is a very exciting technology that is only just now starting to become accessible to the DIY market. Think radar, but with lasers. There’s a few different modules starting to pop up for just a few hundred dollars. But what is one to do with a LIDAR module? Well, [David] decided to build a room scanner with his Garmin LIDAR Lite, and it’s a wonderful sight to behold.

The scanner consists of a rotating platform, which is driven by a stepper motor. The platform then contains a second motor which runs a tilt axis, upon which the LIDAR is mounted. By aiming the LIDAR in various directions, and recording the detected range, it’s possible to build a point cloud representation of the surrounding area.

The build uses a couple of STM32 chips to do motor control and interface with the LIDAR, but where this build really shines is the mechanical side of things. [David] goes into serious detail about the machining of the parts that make up the rotating system, and there’s plenty of cool bits and pieces like slip rings to make it all work. There’s even some home casting going on here! Be warned, though: there’s some rather juicy close-ups of lathes in action, so put the kids to bed before watching this one all the way through.

We love to see a well-executed build, and even more so when we get to watch the intricate details of how it came together. If you’re still looking for some more inspiration, we’ve seen other LIDAR room scanners before, too.

Simple Quadcopter Testbed Clears The Air For Easy Algorithm Development

June 28, 2018 by Ben James 1 Comment

We don’t have to tell you that drones are all the rage. But while new commercial models are being released all the time, and new parts get released for the makers, the basic technology used in the hardware hasn’t changed in the last few years. Sure, we’ve added more sensors, increased computing power, and improved the efficiency, but the key developments come in the software: you only have to look at the latest models on the market, or the frequency of Git commits to Betaflight, Butterflight, Cleanflight, etc.

With this in mind, for a Hackaday prize entry [int-smart] is working on a quadcopter testbed for developing algorithms, specifically localization and mapping. The aim of the project is to eventually make it as easy as possible to get off the ground and start writing code, as well as to integrate mapping algorithms with Ardupilot through ROS.

The initial idea was to use a Beaglebone Blue and some cheap hobby hardware which is fairly standard for a drone of this size: 1250 kv motors and SimonK ESCs, mounted on an f450 flame wheel style frame. However, it looks like an off-the-shelf solution might be even simpler if it can be made to work with ROS. A Scanse Sweep LIDAR sensor provides point cloud data, which is then munched with some Iterative Closest Point (ICP) processing. If you like math then it’s definitely worth reading the project logs, as some of the algorithms are explained there.

It might be fun to add FPV to this system to see how the mapping algorithms are performing from the perspective of the drone. And just because it’s awesome. FPV is also a fertile area for hacking: we particularly love this FPV tracker which rotates itself to get the best signal, and this 3D FPV setup using two cameras.