Skip to content
View mkner's full-sized avatar

Block or report mkner

Block user

Prevent this user from interacting with your repositories and sending you notifications. Learn more about blocking users.

You must be logged in to block users.

Please don't include any personal information such as legal names or email addresses. Maximum 100 characters, markdown supported. This note will be visible to only you.
Report abuse

Contact GitHub support about this user’s behavior. Learn more about reporting abuse.

Report abuse

Pinned Loading

  1. longitudinal-vehicle-dynamics longitudinal-vehicle-dynamics Public

    Tutorial notebook for automotive longitudinal physics and dynamics. Includes test scenarios for various 2-dimensional terrain and throttle profiles. Parameters can be changed to experiment with the…

    Jupyter Notebook 6

  2. road-network-paths road-network-paths Public

    Shortest road network paths with Open Street Map using a Dijkstra/A* Combo Algorithm

    Jupyter Notebook 1

  3. visual-environmental-perception-for-autonomous-vehicles visual-environmental-perception-for-autonomous-vehicles Public

    Visual environmental perception methods for autonomous road vehicles using semantic segmentation to discover drivable surfaces, lane boundaries, and distances to dynamic and static objects

    Jupyter Notebook 1

  4. visual-odometry visual-odometry Public

    Comparison of visual odometry transformation reconstruction methods for optimal path estimates and localization using feature detection, description, matching and trajectory generation

    Jupyter Notebook 1

  5. longitudinal-and-lateral-controllers-for-autonomous-vehicles longitudinal-and-lateral-controllers-for-autonomous-vehicles Public

    Longitudinal and lateral controllers for autonomous vehicles. Features PID and enhanced Stanley controllers. Implementation is for CARLA simulator.

    Python 6 1

  6. basic-pid basic-pid Public

    A Python PID controller that is easy to use, works and does the job. The PID controller implements timestep integration that is designed to be used in discrete-time regulators.

    Python