Term 2

Sensor Fusion

Sensors: Learn how lidar and radar work.

  • Kalman Filter:
    Use probability distributions to fuse lidar and radar data together.
  • C++ Tutorial:
    Review the key C++ concepts for implementing the Term 2 projects.
  • Kalman Filter in C++:
    Build high performance filters.
  • Project: Pedestrian Tracking

Fuse sanitized lidar and radar data together to track a pedestrian.

  • Unscented Kalman Filter:
    Fuse sensor nonlinear measurements.
  • Project: Pedestrian Tracking

Fuse real-world lidar and radar data together to track a pedestrian.


  • Motion: Study
    how motion and probability affect your belief about where you are in the world.
  • Markov Localization:
    Use a Bayesian filter to localize the vehicle.
  • Bayesian Filter:
    Implement a Bayesian filter for localization.
  • Egomotion:
    Estimate the position of the car over time given different sensor data.
  • Sampling for Localization:
    Use a particle filter to localize the vehicle.
  • Particle Filter:
    Implement a particle filter in C++.
  • Project: Kidnapped Vehicle

Implement a particle filter to take real-world data and localize a lost vehicle.


  • Stability:
    Investigate the properties of stable and unstable systems.
  • Open-Loop Control:
    Implement a controller in which the actuation is independent of the controller output.
  • Closed-Loop Control:
    Implement a controller in which the actuation is dependent on the controller output.
  • PID Controller:
    Implement a Proportional-Integral-Derivative controller.
  • Linear Quadratic
    Regulator: Optimize the PID controller using a quadratic system of equations.
  • Project: Lane-Keeping

Implement a controller to overcome disturbances and keep a simulated vehicle in its path.

  • Vehicle control
    Kinematic and dynamic vehicle models.
  • Model predictive control
    Frame the control problem as an optimization problem over time horizons.
  • Project: Model predictive control

Drive the vehicle around the track even with the additional latency between commands!


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