The Microsoft Kinect's range of uses that have been reported represent just the tip of the proverbial iceburg. I'm certain we will see it being used for many more applications, including those within the areas of robotics.
Respectfully, you may have a misconception about LabVIEW that is (unfortunately) somewhat common. Many people assume that LabVIEW provides an interpreted programming approach because the code is largely represented graphically instead of through text.
The truth is that "G" (i.e. graphical code) in LabVIEW has been a compiled language for several decades now. At the end of code compilation, LabVIEW code is converted into machine code in the same manner as other programming languages. LabVIEW now uses a very powerful, open-source compiler known as LLVM that is also used by industry leaders like Apple, Adobe and Sun Microsystems.
In addition to being able to compile to machine code, LabVIEW code can also be compiled to run on silicon in the form of FPGAs. The reliablity and performance achieved through FPGAs have made popular as part of the control systems in many robotics and mechatronics systems.
You can read more about the LabVIEW compiler here:
I think the idea of extending vision-based gesture recognition to industrial robots makes a lot of sense. We've written about use of the Kinect vision sensor, a major new input device for vision-based gesture recognition, applied to robotics, as well as this robotic gesture-recognition software based on a 3D bend-and-twist fiber optics sensor used in the film industry for motion capture: http://www.designnews.com/author.asp?section_id=1386&doc_id=245683 Interestingly, those researchers said their next rev would be Kinect-based. A different approach we wrote about would help industrial robots predict humans' next moves in assembly based on a decision-tree algorithm: http://www.designnews.com/author.asp?section_id=1386&doc_id=246646 A member of the Embedded Vision Alliance (whose representatives lectured at our recent Digi-Key CEC on embedded vision) has also written this article on vision-based gesture recognition focusing on Kinect, which also discusses software: http://www.digikey.com/us/en/techzone/microcontroller/resources/articles/vision-based-gesture-recognition.html
I agree naperlou - while higher level languages are convenient and typically much easier to use (loved CEC's Testpoint back in the day), nothing beats the control you can get at the lower levels. This coming from someone who still uses assembly when programming PICs- love moving those bits around!
Jon, your idea is interesting, but I think it needs a lot more investigation before being implemented. As for programming the robots, even when you have these high level languages, as in LabView, the code you write is internally stored in a form more like the "older" styles of code you mention. In the end, these things have to be translated into something a computer can understand. That means a formal language that can be compiled, optimized and translated into machine code.In the end, these codes also have to be precise and provable. I see a lot of higher level languages used, but still the lower level ones are needed to do things the developers of the high level codes did not anticipate.
New versions of BASF's Ecovio line are both compostable and designed for either injection molding or thermoforming. These combinations are becoming more common for the single-use bioplastics used in food service and food packaging applications, but are still not widely available.
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 radio show will show what’s possible with smart machines, and what tradeoffs need to be made to implement such a solution.