Recently, I read some articles about deep learning being implemented to the industrial robots. I am not sure if anyone here has any first hand experience on this topic. I always think deep learning is very computing power intensive and may not be able to be handled by the robot controllers. Also, robot programming is not C++ or Python programming. Deep learning library cannot be installed on the robot controller as it can be installed on the regular PC. I just didn't see how the deep learning or machine learning algorithm can be implemented to the industrial robots.
Deep learning and robot programming?
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stephen127 -
November 16, 2016 at 8:59 PM -
Thread is marked as Resolved.
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Most industrial controllers are not equipped to do this type of thing, but they can easily be linked to higher-level controllers that can.
While I have yet to encounter it myself, I imagine that one of the first applications would be in Machine Vision -- being able to identify, and then reliably grasp, randomly-placed parts, especially when piled haphazardly together (bin picking), is one of the Holy Grails of industrial robotics.
Fanuc appears to have a self-teaching robot for this kind of application: https://www.technologyreview.com/s/601045/this-…-job-overnight/I could imagine this kind of technique being applied to industrial robots to improve their spatial accuracy. I've recently had to put a lot of work into using metrology to measure 3-D accuracy corrections across a large volume for an industrial robot. While my application did not use deep learning, I could easily imagine an application where, if the measurement was automated, a robot could teach itself corrections to a high level of accuracy across its motion envelope.
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Living in a dynamic physical world, it’s easy to forget how effortlessly we understand our surroundings. With minimal thought, we can figure out how scenes change and objects interact.
But it is still a huge problem for machines. With the limitless number of ways that objects can move, teaching computers to predict future actions can be difficult.
Recently, researchers from MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) have moved a step closer, developing a deep-learning algorithm that, given a still image from a scene, can create a brief video that simulates the future of that scene.
Trained on 2 million unlabeled videos that include a year’s worth of footage, the algorithm generated videos that human subjects deemed to be realistic 20 percent more often than a baseline model.
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You can do robot programming using Python or C# with RoboDK.
For example, the same program in Python or C# can be used to:
1- Simulate in the RoboDK graphical environment
2- Generate a robot program using a post processor (offline programming)
3- Run the program on the real robot synchronized with the computer (using robot drivers)More information regarding offline programming with Python here:
http://www.robodk.com/offline-programming -
You can do robot programming using Python or C# with RoboDK.
For example, the same program in Python or C# can be used to:
1- Simulate in the RoboDK graphical environment
2- Generate a robot program using a post processor (offline programming)
3- Run the program on the real robot synchronized with the computer (using robot drivers)More information regarding offline programming with Python here:
http://www.robodk.com/offline-programming
Thanks Albert. I'm a newbie to programming robots..can you state the steps to programming an industrial robot please? So design mechanical robotic arms/system, based on that info write code on python and robodk will convert the code for simulation and based on the output we make corrections and finalise for real world testing? Fairly accurate?
Many thanks.
AdhiSent from my SM-G925I using Tapatalk