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Showing posts from November, 2018

Info on Wi-Fi Disconnects for Motorola E4, G5, and G5 Plus Android Phones

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The Motorola E4 phone is approved for use in the  FIRST  Tech Challenge. In fall 2018, teams reported seemingly random disconnects between the Driver Station and Robot Controller devices when the E4 phones were used. Note that although this issue was first reported with the Motorola E4 phone, it also occurs with the Motorola G5 and G5 Plus phones.   The disconnects can occur when the Motorola E4 phone is acting as the Driver Station, and an op mode has been selected and initialized, but not started.  In this situation, if the Robot Controller  waits for a  start  command from the Driver Station, the phones might momentarily disconnect and cause the op mode run to stop before the start command is received.   There is a solution to this problem.  It involves rewriting your op mode so that the Robot Controller sends telemetry messages to the Driver Station while it is waiting for the start command.  Doing this seems to prevent the devices from momentarily disconnecting.   Details on h

TensorFlow Machine Learning Technology is Now Available for Teams!

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FIRST Tech Challenge Tech Update:   Teams participating in the FIRST Tech Challenge can now use Google�s TensorFlow Machine Learning technology to detect and track Gold and Silver game elements. Teams can access Google�s TensorFlow technology through Blocks or Java programming.   TensorFlow can identify Gold and Silver game elements using an Android device�s built in camera or through an externally connected camera. A detailed tutorial is available that demonstrates how to use this TensorFlow technology is available here!  TensorFlow is Google's "machine learning" technology. It is a form of artificial intelligence. The software can "learn" and identify patterns and use this to do things like recognize when a Gold block is placed in front of the camera. For our software, Google "trained" the system (by showing it pictures of our Gold and Silver blocks in different positions and under different lighting conditions and backgrounds) so it would learn what