Cisco Teams Up with Robotics Firm Fanuc for IoT

by Zacks Equity Research:  Technology giant and Dow component Cisco Systems, Inc. recently entered into a strategic alliance with a robotics company Fanuc America, thereby stepping up its efforts to make itself a key player in the Internet of Things (IoT) space. 

Per the alliance, Fanuc and Cisco have built an IoT system that enables Fanuc to monitor every robot on the factory floor. This way it can be determined whether a robot is likely to fail, so that a service technician can fix the equipment before it stops working.

This could save companies hundreds of dollars of fixing cost. Per Cisco CEO Chuck Robbins, downtime for these robots can cost a business $16,000 per minute. Therefore, the new system that offers predictive maintenance can be a big thing for some operations.

The companies are currently testing the system in a channel that comprises around 1,800 robots and includes Fanuc customer, GM. In this testing period, Fanuc says its customer has saved $38 million. Fanus has plans to expand the system to 2,500 robots by the end of the year. Cont'd...

Drones in the Water

Essentially, we're creating drones for water that produce mapping capabilities; it's somewhat similar to air drones (i.e.: fixed wing UAVs) that map from the sky, but we're mapping from the water.

Grizzly - Robotic Utility Vehicle (RUV)

We build all our robots around a popular open source robotics development framework, called Robot Operating System (ROS). Since it is open source, it makes it quite simple to integrate with other open source initiatives, like Android.

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Mission Impossible: Mining The Ocean

Working at extreme ocean depths presents a myriad of problems, which will still take years to overcome. To be truly successful, AUVs will have to be totally autonomous and free moving without the restraints of tethers. As we use up our resources on land, the oceans are the next frontier. The most important question is "How will ocean mining effect the environment?"

Object Reconstruction And Recognition Leveraging An RGB-D Camera Like The Kinect

Recently, so-called RGB-D cameras have become available, capable of delivering synchronized color (RGB) and depth (D) information in real-time. The depth information is dense, and comes at negligible additional processing cost for the host CPU. They avoid the complexity of robust disparity map computation of stereo systems, and are much faster than laser scanning techniques. Thus, these sensors are very attractive for the computer vision community and their benefits to classical applications are worth investigating.

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