Specializations

Contents

• Coprocessor
  • Packaging
• Machine Learning
  • Dec 4 - Introduction
  • Dec 11 - Convolutional Neural Networks
• Algorithms
  • C++ lessons
  • Kalman Filters
• Math/physics modeling
  • Basic calculus

Robot control will include working with WPILib, CTRE Phoenix Framework, REVLib, and Advantage Scope. Focus would be on knowing everything regarding swerve drive, motor control, Phoenix V6, PIDf, SysID, kinematics, power delivery, and some electrical knowledge. Very important and needs most people.

Coprocessor deployment and maintenance will include working with Linux, Debian, Docker, Conda, Bash, and CMake. Focus would be on automating integration and deployment. Important for vision but doesn’t need many people.

Vision (machine learning) will include working with PyTorch, Tensorflow, OpenCV, and YOLO. Focus would be on object detection, foreground segmentation, and depth estimation. Somewhat important but doesn’t need many people.

Vision (algorithms and networking) will include working with C/C++, OpenCV, CMake, general Linux. Focus would be on AprilTags with OpenCV, setting up camera streams with V4L2, and low-level networking in UDP. Revolves around low-level programming and linear algebra. People under this field will be contributors to Titan Processing. Important but doesn’t need many people.

Math and physics modeling will include solving problems with control theory, linear algebra, calc-based physics, multi-variable calculus, and more. Heavy on specific topics like control theory, inverse kinematics, and Kalman filters. Important for subsystems and would require at least a couple people.