• Released on: 10/15
• Due on: 11/04 (by midnight)

There are three objectives for this project:

1. Become familiar with and implement an advanced path planning algorithm.
2. Become familiar with modelling for activity planning.
3. Understand the interplay between path and activity planning.

The code for 16.413 students is being kept on a separate branch of the repo used for the course (so as to not clutter the path of people in 16.410). Run the following commands to switch branches. Remember the default password (needed for sudo) is 'student'.

cd /etc/chef
sudo git fetch
sudo git checkout 16.413

After this, run sudo update_intro_to_autonomy as usual.

This project uses the command line heavily and we need to set up a Python virtualenv to use for this project. To do so, run the following commands. Note that the first command has two >s, not one!

echo "source /usr/share/virtualenvwrapper/virtualenvwrapper.sh" >> ~/.bashrc
# Close and then reopen any terminals you have open at this point.
mkvirtualenv proj1
workon proj1
pip install -i /home/student/jupyter/projects/project1/requirements.txt
# The previous step may take quite a bit of time.
add2virtualenv /home/student/jupyter/projects/project1/py

From now on, any time you open a terminal to work on this project, you need to make sure all the Python libraries are on your path by running:

workon proj1

The project is located in the ~/jupyter/projects/project1 folder.

The Python code is located in py/.

bin/ contains executables.

rmpl/ is where RMPL scripts should be located.

environments/ is where environment files should be located.

Choose a path planning algorithm.

Implement the algorithm.

Remember that you can post questions in our Piazza Forum. Please do not post answers to the problems, though.