This is a two-part video on “A Brief History of 3D Vision Technologies”. Click here for Part 2 on sheet of light, co-planar, stereo vision, LiDAR, and X-ray scanners.
Light Curtain
So one of the oldest and simplest methods of 3D measurement, and this was used very widely in the wood industry is what’s called the light curtain. And this was the first product that my company made. Basically, what this consists of is a bank of emitters. And you can see the bank of emitters would exist over on the left here. And then a bank of detectors, which would exist over on the right here. And these emitters emit light via some source, typically an LED or laser diode, emit light. And that light will propagate over to where the detectors are. And if there’s any object in the way, then it will block the detectors on the other side. And so are the detectors are dark, it means there’s an object there, and you would get a dimension across that object. Now, it doesn’t give you any idea of what that shape of that object is other than the most extreme dimensions. But you can use multiple banks of these light curtains to get dimensions and multiple planes. And the setup you see right here was very common in the wood industry back in the early 90s, where you’d have two banks set up. And that would allow you to get these four points shown in purple around a log and give you a rough idea of what are the dimensions or what is the kind of representative ellipse at a given time when this log is moving through this bank of light curtains.
Single Point Depth Measurement
The next logical step after the light curtain is a single point depth measurement. Being able to measure depth using a single point proved to be a very powerful tool for real-time dimensional monitoring, say something like, you know, planar mill, but we’ll get to that in one minute. Basically, what this type of device consists of is the device itself, which is shown over here in blue, and that emits a single laser beam, a single collimated laser beam kind of like a laser pointer out from its face. And then if there is an object that it hits, say, a board, for example, some of that light will hit that object and bounce back towards a camera in device, or what we’ll call an imager here. And then if that object were, say, in a different position, maybe a couple of inches farther out, that same laser would hit a different position within the imager. And what you’ll notice here, these are triangles. So this ends up being very much a geometric measurement where we can, we can calibrate any position in this imager to a given depth. And we can do that very, very accurately to submillimeter accuracy, and get a very high-quality result. And that’s largely because it’s based on very solid geometries. So here’s a good example of where we’re using an imager or a camera that captures intensity. And then using that in conjunction with structured light, to get a 3D measurement. This is a very common way of getting 3D measurements. And there’s lots of different devices that use this geometric property of positioning some sort of light source with some sort of imager, and getting data back.
Shown here is a mock-up of a planer mill, where in real-time using three or four of these devices, you can monitor the dimensions of a board. And if anything’s out of dimension, you know it in real-time. And this was a big step up from having somebody go once or a couple of times a shift checking with callipers or with some manual measurement method if the dimensions were on or off, and by having this be real-time, if they were off, you knew right away and you could have the machine center adjust itself, and you wouldn’t have a lot of undersized or oversized products that you had to deal with. shown over here is a model of what we call the LRS-50. It’s one of the products we make it’s very small, it can basically sit in the palm of your hand. This is an example of a single point sensor. There are quite a number of these on the market. So you might run into a number of different examples of these in your careers.
Watch Part 2 of the lecture here.
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