Improving the effectiveness of small and medium manufacturers could help stimulate the economy and drive job creation. Adding robotic employees to the manufacturing mix might just make manufacturers in the United States more competitive with their counterparts in Asia.
MIT Technology Review: Fanuc’s robot uses a technique known as deep reinforcement learning to train itself, over time, how to learn a new task. It tries picking up objects while capturing video footage of the process. Each time it succeeds or fails, it remembers how the object looked, knowledge that is used to refine a deep learning model, or a large neural network, that controls its action. Deep learning has proved to be a powerful approach in pattern recognition over the past few years.
“After eight hours or so it gets to 90 percent accuracy or above, which is almost the same as if an expert were to program it,” explains Shohei Hido, chief research officer at Preferred Networks, a Tokyo-based company specializing in machine learning. “It works overnight; the next morning it is tuned.”... ( full story )
What do ants and Industry 4.0 have in common? What challenges faced the engineers when it came to developing these delicate technology platforms? Take a look behind the scenes and dive into the world of the Bionic Learning Network... ( cont'd )
The Model 30MT is a compact magnetic encoder module designed for the most extreme environments. It offers sealing up to IP69K, an operating temperature range of -40° to 120° C, and a shock and vibration rating that conforms to Mil-STD-202G. With a large air gap and tolerance to misalignment, up to 1024 CPR (4096 PPR with Quadrature Counting), and easy alignment and installation, the Model 30M or is an excellent solution where you need motion feedback in your robotics application.