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The Data Acquisition Blog is the place for conversation and discussion about signal conditioning components and systems, digital and analog I/O modules, signal and data conversion and data acquisition software. Here, you'll find everything from application ideas, to news and industry trends, to hot topics and cutting edge innovations. This blog is inspired by the Data Acquisition newsletter from GlobalSpec, which you can subscribe to here.

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Apprenticeship Learning in Factory Automation

Posted January 17, 2009 8:08 AM

Stanford University researchers have been experimenting with designing a robotic radio-controlled model helicopter that can fly autonomously, as described in this LiveScience posting — which has a link to video of the helicopter in flight. The researchers' approach is to use an artificial intelligence technique called "apprenticeship learning," in which the prototype automated control system first "watches" an expert human operator fly the helicopter through various aerobatic maneuvers, while it compares the control inputs to the resulting motions of the aircraft. A number of accelerometers, gyroscopes, and magnetometers help the control system monitor helicopter position and acceleration in three dimensions.

The researchers have published a paper that discusses the control issues addressed.

What do you think? Would such apprenticeship learning have application in factory automation?

The preceding article is a "sneak peek" from Data Acquisition, a newsletter from GlobalSpec. To stay up-to-date and informed on industry trends, products, and technologies, subscribe to Data Acquisition today.


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Power-User

Join Date: Apr 2008
Location: Lexington, KY
Posts: 344
Good Answers: 14
#1

Re: Apprenticeship Learning in Factory Automation

01/19/2009 12:33 PM

I can't see how this autonomous control method would be useful in a factory except for moving around in open space. And moving around in open space is always dangerous if you are unaware of changes to your environment. The control system would have to improvise for impediments and safety devices would have to be included to the extent that it would no longer be autonomous.

That being said, there is the problem of precision and accuracy. There are already several types of devices that are programmed via a "teach" method of some kind or another. These devices can then search for position information so that it can perform some function using the actual location instead of the expected location. This is necessary because variation in manufacturing is a fact of life and is both normal and expected. Autonomy does not imply the ability to deal effectively with variation, unless it also uses some sort of vision system or equavalent sensor network.

Lastly, robotic autonomy requires additional intelegence such as "crash avoidance" and "escape route planning" should it have to abort some movement. Even a sudden stop, in mid-air, does not guarantee that something behind it will avoid it as well. To be safe, there are many more variables that must be monitored. Or, it can just exist within the confines of a cage like other good robots. Most machines would not survive the consequences of a bad decision.

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