Autonomous Vehicles Nano Degree

Udacity Nano-Degree program on Autonomous Vehicles. There are several projects in this nanodegree and each project has its own branch. All of these branches can be found within AutonomousVehicles repository. Listed below is brief description of each of those projects.

Lane Line Detection

1. Finding lane lines on the road project is located here.
2. The first part of the challenge, which includes detecting the lane lines and extrapolating the segmented lines to a solid line and running lane detection pipeline on a video stream can be found in FindingLaneLines.py
3. The second part of the challenge, which include detecting the lane lines for curved lane scenraio can be found in curvedLaneFinding.py

Advanced Lane Line Finding

1. Source code for Advanced Lane Line finding algorithm is found here
2. Output images from the algorithm are saved here
3. Follow the writeup here to get a brief explanation of the algorithm and how to run the code

Traffic Sign Classifier

1. This project was developed on Ipython notebook and it located here
2. The test images downloaded from web to test on the model is located here
3. The writeup for this project is located here
4. Note that the pickle file with augmented data set is not uploaded on the repository due to file size constraints. If you want to download this project and run, please contact me.

Behavioral Cloning

1. Source code for this project and its neural network architecture can be found inside source directory
2. Data used to train the model can be found inside data directory
3. A writeup for this project can be in the markdown file named writeup_behavioral_cloning
4. The images used for the writeup can be found in the directory writeup_images
5. An output video of the car driving autonomously in two tracks can be found in the directory video

Extended Kalman Filter

1. Source code for EKF algorithm can be found in the src directory
2. Once the install for uWebSocketIO is complete, the main program can be built and run by doing the following from the project top directory.
   • mkdir build
   • cd build
   • cmake ..
   • make
   • ./ExtendedKF

Particle Filter

1. The source code for this project is located here
2. On the parent directory, clean.sh cleans the build
3. build.sh, builds the project
4. On successful build, the project can be run using run.sh
5. Turn on the simulator and navigate to "Kidnapped Vehicle" simulation and hit the start button
6. You should see blue and green lines almost align with each-other marking coherence to groundtruth
7. The project is marked successful if the error is within range and the car completes three loops within 100 seconds

Path Planning

1. The source code for this project is located here
2. Please take a look at the Readme for this project, located on the main page of the path_planning branch
3. Read me contains the build instructions and algorithm overview

PID Controller

1. The souce code for this project is located here
2. Please take a look at the Readme for this project to get an overview of PID controller's implementation details

Capstone Project

1. Navigate to the main page and review the Readme before continuing
2. All the ROS nodes responsible for running this project are located in the src directory
3. Follow Readme to download and run this project