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Theory behind Robotics

The following pages will provide an overview of the following important topics of robotics: For more details be sure to check out the Self Driving cars with Duckietown edX MOOC. Also don't forget to read through the resources listed on the main page of this documentation and consult your robotics engineering text books of choice.

  • Modeling and Control

    • Introduction to control systems
    • Representations and models
    • PID control
  • Robot Vision

    • Introduction to projective geometry
    • Camera modeling and calibration
    • Image processing
  • Object Detection

    • Convolutional neural networks
    • One and two stage object detection
  • State Estimation and Localization

    • Bayes filtering framework
    • Parameterized methods (Kalman filter)
    • Sampling-based methods (Particle and histogram filter)
  • Planning I

    • Planning formalization
    • Graphs
  • Planning II

    • Probabilistic roadmaps
    • Sampling-based planning
  • Learning by Reinforcement

    • Markov decision processes
    • Value functions
    • Policy gradients
    • Domain randomization
  • Learning by Imitation

    • Behaviour cloning
    • Online imitation learning
    • Safety and uncertainty