That's a valid question. There's more than one way to create 3D in machine vision. Chuck's upcoming February feature, already out in the print edition of DN, discusses this subject. The simplest, easiest, cheapest method is by using two 2D cameras in stereo, as does this QuantumVision product. This roughly emulates the stereoscopic vision of humans (and other primates), in that both of our eyes used together creates 3D stereo images. Others use more complex math and/or special image sensors, and/or special image processing.
Basically, this is smaller than other stereo 3D cameras, and it's way smaller than other 2-camera 3D stereo cameras. Since it's a stereo 3D system, it's created with two 2D cameras, so there's really no new paradigm in that sense; you are still processing 2D data. You can process that data faster if you use the cameras independently. Another thing about this system is its rugged enclosure, which is why it's shown with water drops.
Ann, what's the use case for this type of system compared with a traditional 2D vision system or any of the stereo 3D systems? Am I saving money by going this route or is it purely a matter of increasing visibility without having to move to a totally new 3D paradigm?
Truchard will be presented the award at the 2014 Golden Mousetrap Awards ceremony during the co-located events Pacific Design & Manufacturing, MD&M West, WestPack, PLASTEC West, Electronics West, ATX West, and AeroCon.
In a bid to boost the viability of lithium-based electric car batteries, a team at Lawrence Berkeley National Laboratory has developed a chemistry that could possibly double an EV’s driving range while cutting its battery cost in half.
For industrial control applications, or even a simple assembly line, that machine can go almost 24/7 without a break. But what happens when the task is a little more complex? That’s where the “smart” machine would come in. The smart machine is one that has some simple (or complex in some cases) processing capability to be able to adapt to changing conditions. Such machines are suited for a host of applications, including automotive, aerospace, defense, medical, computers and electronics, telecommunications, consumer goods, and so on. This discussion will examine what’s possible with smart machines, and what tradeoffs need to be made to implement such a solution.