/CarND-MPC-Project

Primary LanguageC++MIT LicenseMIT

CarND-Controls-MPC

Self-Driving Car Engineer Nanodegree Program


Dependencies

Basic Build Instructions

  1. Clone this repo.
  2. Make a build directory: mkdir build && cd build
  3. Compile: cmake .. && make
  4. Run it: ./mpc.

Build with Docker-Compose

The docker-compose can run the project into a container and exposes the port required by the simulator to run.

  1. Clone this repo.
  2. Build image: docker-compose build
  3. Run Container: docker-compose up
  4. On code changes repeat steps 2 and 3.

Tips

  1. The MPC is recommended to be tested on examples to see if implementation behaves as desired. One possible example is the vehicle offset of a straight line (reference). If the MPC implementation is correct, it tracks the reference line after some timesteps(not too many).
  2. The lake_track_waypoints.csv file has waypoints of the lake track. This could fit polynomials and points and see of how well your model tracks curve. NOTE: This file might be not completely in sync with the simulator so your solution should NOT depend on it.
  3. For visualization this C++ matplotlib wrapper could be helpful.)
  4. Tips for setting up your environment are available here
  5. VM Latency: Some students have reported differences in behavior using VM's ostensibly a result of latency. Please let us know if issues arise as a result of a VM environment.

Editor Settings

We have kept editor configuration files out of this repo to keep it as simple and environment agnostic as possible. However, we recommend using the following settings:

  • indent using spaces
  • set tab width to 2 spaces (keeps the matrices in source code aligned)

Code Style

Please (do your best to) stick to Google's C++ style guide.

Ipopt and CppAD usage

Please refer to here to see how Ipopt works, or you can reach my repo to tease with this library, in this repo, you can use C++ matplotlib wrapper to see how Ipopt optimize the control input for you.

Snippet

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