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.

Visible Light CT Scanner Does Double Duty

March 17, 2018 by Dan Maloney 21 Comments

If you’ve ever experienced the heartbreak of finding a seed in your supposedly seedless navel orange, you’ll be glad to hear that with a little work, you can protect yourself with an optical computed tomography scanner to peer inside that slice before popping it into your mouth.

We have to admit to reading this one with a skeptical eye at first. It’s not that we doubt that a DIY CT scanner is possible; after all, we’ve seen examples at least a couple of times before. The prominent DSLR mounted to the scanning chamber betrays the use of visible light rather than X-rays in this scanner — but really, X-ray is just another wavelength of light. If you choose optically translucent test subjects, the principles are all the same. [Jbumstead]’s optical CT scanner is therefore limited to peeking inside things like slices of tomatoes or oranges to look at the internal structure, which it does with impressive resolution.

This scanner also has a decided advantage over X-ray CT scanners in that it can image the outside of an object in the visible spectrum, which makes it a handy 3D-scanner in addition to its use in diagnosing Gummi Bear diseases. In either transmissive or reflective mode, the DSLR is fitted with a telecentric lens and has its shutter synchronized to the stepper-driven specimen stage. Scan images are sent to Matlab for reconstruction of CT scans or to Photoscan for 3D scans.

The results are impressive, although it’s arguably more useful as a scanner. Looking to turn a 3D-scan into a 3D-print? Photogrammetry is where it’s at.

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Four Pi Zeros, Four Cameras, One Really Neat 3D Scanner

January 17, 2018 by Jenny List 24 Comments

Sometimes when you walk into a hackerspace you will see somebody’s project on the table that stands so far above the norm of a run-of-the-mill open night on a damp winter’s evening, that you have to know more. If you are a Hackaday scribe you have to know more, and you ask the person behind it if they have something online about it to share with the readership.

[Jolar] was working on his 3D scanner project on just such an evening in Oxford Hackspace. It’s a neatly self-contained unit in the form of a triangular frame made of aluminium extrusions, into which are placed a stack of Raspberry Pi Zeros with attached cameras, and a very small projector which needed an extra lens from a pair of reading glasses to help it project so closely.

The cameras are arranged to have differing views of the object to be scanned, and the projector casts an array of randomly created dots onto it to aid triangulation from the images. A press of a button, and the four images are taken and, uploaded to a cloud drive in this case, and then picked up by his laptop for processing.

A Multi-view Stereo (MVS) algorithm does the processing work, and creates a 3D model. Doing the processing is VisualSFM, and the resulting files can then be viewed in MeshLab or imported into a CAD package. Seeing it in action the whole process is quick and seamless, and could easily be something you’d see on a commercial product. There is more to come from this project, so it is definitely one to watch.

Four Pi boards may seem a lot, but it is nothing to this scanner with 39 of them.

A 3D Scanner That Archimedes Could Get Behind

July 14, 2017 by Dan Maloney 48 Comments

3D-scanning seems like a straightforward process — put the subject inside a motion control gantry, bounce light off the surface, measure the reflections, and do some math to reconstruct the shape in three dimensions. But traditional 3D-scanning isn’t good for subjects with complex topologies and lots of nooks and crannies that light can’t get to. Which is why volumetric 3D-scanning could become an important tool someday.

As the name implies, volumetric scanning relies on measuring the change in volume of a medium as an object is moved through it. In the case of [Kfir Aberman] and [Oren Katzir]’s “dip scanning” method, the medium is a tank of water whose level is measured to a high precision with a float sensor. The object to be scanned is dipped slowly into the water by a robot as data is gathered. The robot removes the object, changes the orientation, and dips again. Dipping is repeated until enough data has been collected to run through a transformation algorithm that can reconstruct the shape of the object. Anywhere the water can reach can be scanned, and the video below shows how good the results can be with enough data. Full details are available in the PDF of their paper.

While optical 3D-scanning with the standard turntable and laser configuration will probably be around for a while, dip scanning seems like a powerful method for getting topological data using really simple equipment.

[wpvideo xx88I1SN]

Thanks to [bmsleight] for the tip.

Amazing 3D-Scanner Teardown And Rebuild

February 6, 2017 by Elliot Williams 14 Comments

Pour yourself a nice hot cup of tea, because [iliasam]’s latest work on a laser rangefinder (in Russian, translated here) is a long and interesting read. The shorter version is that he got his hands on a broken laser security scanner, nearly completely reverse-engineered it, got it working again, put it on a Roomba that was able to map out his apartment, and then re-designed it to become a tripod-mounted, full-room 3D scanner. Wow.

The scanner in question has a spinning mirror and a laser time-of-flight ranger, and is designed to shut down machinery when people enter a “no-go” region. As built, it returns ranges along a horizontal plane — it’s a 2D scanner. The conversion to a 3D scanner meant adding another axis, and to do this with sufficient precision required flipping the rig on its side, salvaging the fantastic bearings from a VHS machine, and driving it all with the surprisingly common A4988 stepper driver and an Arduino. A program on a PC reads in the data, and the stepper moves another 0.36 degrees. The results speak for themselves.

This isn’t [iliasam]’s first laser-rangefinder project, naturally. We’ve previously featured his homemade parallax-based ranger for use on a mobile robot, which is equally impressive. What amazes us most about these builds is the near-professional quality of the results pulled off on a shoestring budget.

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Milk-Based 3D Scanner

April 16, 2016 by Elliot Williams 32 Comments

3D scanners don’t have to be expensive or high-tech because all of the magic goes on in software. The hardware setup just needs to gather a bunch of cross-sections. In perhaps the lowest-tech of scanners that we’ve seen, [yenfre]’s GotMesh scanner uses milk.

Specifically, the apparatus is a pair of boxes, one with a hole drilled in it. You put the object in the top box and fill it with milk to cover the object. A camera takes pictures of the outline of the object in the milk as it drains out the hole, these get stitched together, and voilà.

There are limitations to this method. The object gets soaked in milk, so it won’t work for scanning sand-castles. (It’s optimally suited for chocolate-chip cookies, in our opinion.) If the camera is located directly above, the objects have to get wider as the milk drains out. You can do multiple takes with the object rotated at different angles or use multiple cameras to solve this problem. The edge-detection software will have issues with white objects in milk, so maybe you’ll want to scan that porcelain figurine in coffee, but you get the idea. More seriously, the rate of milk drain will slow down a bit as the amount of milk in the upper box decreases. This could also be handled in software.

In all, we’re not surprised that we don’t see commercial versions of this device, but we love the idea. It’s based on this experiment where they dip a guy in a tank of ink! If you just drank all your milk, but still have a line-laser lying around, maybe this build is more your speed. What’s your cheapest 3D scanner solution?

Polarizing 3D Scanner Gives Amazing Results

December 23, 2015 by Al Williams 16 Comments

What if you could take a cheap 3D sensor like a Kinect and increase its effectiveness by three orders of magnitude? The Kinect is great, of course, but it does have a limited resolution. To augment this, MIT researchers are using polarized measurements to deduce 3D forms.

The Fresnel equations describe how the shape of an object changes reflected light polarization, and the researchers use the received polarization to infer the shape. The polarizing sensor is nothing more than a DSLR camera and a polarizing filter, and scanning resolution is down to 300 microns.

The problem with the Fresnel equations is that there is an ambiguity so that a single measurement of polarization doesn’t uniquely identify the shape, and the novel work here is to use information from depth sensors like Kinect to select from the alternatives.

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