juanlvo / CarND-MPC-Project

CarND Term 2 Model Predictive Control (MPC) Project

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CarND-Controls-MPC

Self-Driving Car Engineer Nanodegree Program solution from Juan Luis Vivas Occhipinti


Dependencies

  • cmake >= 3.5
  • All OSes: click here for installation instructions
  • make >= 4.1
  • gcc/g++ >= 5.4
  • uWebSockets
    • Run either install-mac.sh or install-ubuntu.sh.
    • If you install from source, checkout to commit e94b6e1, i.e.
      git clone https://github.com/uWebSockets/uWebSockets 
      cd uWebSockets
      git checkout e94b6e1
      
      Some function signatures have changed in v0.14.x. See this PR for more details.
  • Fortran Compiler
    • Mac: brew install gcc (might not be required)
    • Linux: sudo apt-get install gfortran. Additionall you have also have to install gcc and g++, sudo apt-get install gcc g++. Look in this Dockerfile for more info.
  • Ipopt
    • Mac: brew install ipopt
      • Some Mac users have experienced the following error:
      Listening to port 4567
      Connected!!!
      mpc(4561,0x7ffff1eed3c0) malloc: *** error for object 0x7f911e007600: incorrect checksum for freed object
      - object was probably modified after being freed.
      *** set a breakpoint in malloc_error_break to debug
      
      This error has been resolved by updrading ipopt with brew upgrade ipopt --with-openblas per this forum post.
    • Linux
      • You will need a version of Ipopt 3.12.1 or higher. The version available through apt-get is 3.11.x. If you can get that version to work great but if not there's a script install_ipopt.sh that will install Ipopt. You just need to download the source from the Ipopt releases page.
      • Then call install_ipopt.sh with the source directory as the first argument, ex: sudo bash install_ipopt.sh Ipopt-3.12.1.
    • Windows: TODO. If you can use the Linux subsystem and follow the Linux instructions.
  • CppAD
    • Mac: brew install cppad
    • Linux sudo apt-get install cppad or equivalent.
    • Windows: TODO. If you can use the Linux subsystem and follow the Linux instructions.
  • Eigen. This is already part of the repo so you shouldn't have to worry about it.
  • Simulator. You can download these from the releases tab.
  • Not a dependency but read the DATA.md for a description of the data sent back from the simulator.

Basic Build Instructions

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

Tips

  1. It's recommended to test the MPC on basic examples to see if your implementation behaves as desired. One possible example is the vehicle starting offset of a straight line (reference). If the MPC implementation is correct, after some number of timesteps (not too many) it should find and track the reference line.
  2. The lake_track_waypoints.csv file has the waypoints of the lake track. You could use this to 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.

Editor Settings

We've purposefully kept editor configuration files out of this repo in order 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.

Project Instructions and Rubric

Note: regardless of the changes you make, your project must be buildable using cmake and make!

More information is only accessible by people who are already enrolled in Term 2 of CarND. If you are enrolled, see the project page for instructions and the project rubric.

Hints!

  • You don't have to follow this directory structure, but if you do, your work will span all of the .cpp files here. Keep an eye out for TODOs.

Call for IDE Profiles Pull Requests

Help your fellow students!

We decided to create Makefiles with cmake to keep this project as platform agnostic as possible. Similarly, we omitted IDE profiles in order to we ensure that students don't feel pressured to use one IDE or another.

However! I'd love to help people get up and running with their IDEs of choice. If you've created a profile for an IDE that you think other students would appreciate, we'd love to have you add the requisite profile files and instructions to ide_profiles/. For example if you wanted to add a VS Code profile, you'd add:

  • /ide_profiles/vscode/.vscode
  • /ide_profiles/vscode/README.md

The README should explain what the profile does, how to take advantage of it, and how to install it.

Frankly, I've never been involved in a project with multiple IDE profiles before. I believe the best way to handle this would be to keep them out of the repo root to avoid clutter. My expectation is that most profiles will include instructions to copy files to a new location to get picked up by the IDE, but that's just a guess.

One last note here: regardless of the IDE used, every submitted project must still be compilable with cmake and make./

Project Rubric

Compilation

Criteria Meets Specifications
Your code should compile. Yes, the code compile without any error.

Implementation

Criteria Meets Specifications
The Model. The model implemented include the x and y coordinate of the vehicle, the orientation angle (psi), the velocity, the cross track error and the psi error (epsi). You can find as well the output of the acceleration and delta (stereling angle). In the model is combine the actual state and the previous timestep base on the equation below: Equations
Timestep Length and Elapsed Duration (N & dt) The parameter were choose after reading recomendations in the forums, after some modifications of the parameter we can see in the case of dt if we set to lower values than 0.1 the vehicle is driving more chaotic also we can see how the vehicle is driving outside of the track, when is bigger we can see how the vehicle is driving so slow actually in the class of MPC we can see recomendation of using dt=0.5 which is quite good but we got the issue with the speed. In the case of N this value also can be found in the class of MPC where was recomended N=10 if we change the value to something lower of higher the vehicle is driving really chaotic driving outside of the track as well. In this case N is the number of Timesteps. Is important as well to take into the consideration the tunning made it by the author with the steering_angle were the division is by 40 instead of 25 because the driving is more accurate than using 25 (this is what he have seen in practice)
Polynomial Fitting and MPC Preprocessing A polynomial is fitted to waypoints with the preprocesses of the waypoints. This can be found it between lines 115 and 122 in the main.cpp
Model Predictive Control with Latency The model is taking into consideration the latency wich is the diference of time since we apply an stereling angle until finally the is puuting in place the angle (because we are using an mechanical system which can't handle instantly the changing of an angle) this can be localize between the lines 105 and 108 in MPC.cpp

Simulation

Criteria Meets Specifications
The vehicle must successfully drive a lap around the track. Yes, the vehicle is drive successfully the track.

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CarND Term 2 Model Predictive Control (MPC) Project


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