FTC CanDo With TensorFlow 20220513

Added Machine Learning Capability

The goal of this program is to enable CanDo to push a gold cub off the arena more quickly by use Tensorflow. Some may say that we are making the program smarter through machine learning. Whether we think the terms "learning" and "smarter" are appropriate, Convolutional Neural Networks are a powerful, import and fun technology to understand. We'll get a hint of what it is about in this lab.

References

Tutorial Videos

• Tutorial - Using TensorFlow to detect game pieces in First Tech Challenge (FTC) robot competitions and explore Machine Learning
• Locate Gold Mineral And Push Demo Video

Epp TensorFlow Projects

• FTC Epp TensorCode
• IEEE TryEnginering resource page Links to the same tutorial above.

Code

Integrated CanDo and TensorFlow Code

The goal of this program is to enable CanDo to push a gold cub off the arena more quickly by use Tensorflow.

• TensorFlowCanDo11.java

Based on Version 6 of CanDo and

• CanDo06.java for the May lab.
• For details see FTC_A_Hint_of_CanDo_-_TBD_20220422#Version_6_Add_Reverse_and_Turn

Bases on this Version of a TensorFlow Object Detection Program

• TestTensorFlowObjectDetectionWebcamEpp.java

Exercises

Exercise 1

• Test recognition for a gold cube under
  • Various lighting
  • Orientations
  • Distances

Exercise 2

• Enhance the TensorFlowCanDo11.java program by making the robot rotate to find a gold mineral.

Exercise 3

• Make the robot stop rotating after it has located the gold mineral.

Exercise 4

• Make the robot push the gold mineral off the arena.
• If the robot overshoots its rotation, make it adjust its aim until the robot is centered in the monitor.