Start-Kit

Join the competition

Log in to the competition website with a GitHub account, and we will automatically create a private GitHub submission repo for you. The repo will be the place where you submit codes. In the My Submission page, you can click "My Repo" to open your GitHub submission repo page.

Clone your submission repo

Clone your submission repo to your local machine. The repo contains starter codes to help you prepare your submission.

$ git clone [email protected]:your_submission_repo_address
$ cd your_submission_repo

Compile the start-kit

Dependencies

• cmake >= 3.16
• libboost >= 1.49.0
• Python3 >= 3.11 and pybind11 >=2.10.1 are recommanded for python interface user.

Install dependencies on Ubuntu or Debian Linux:

sudo apt-get update
sudo apt-get install build-essential libboost-all-dev python3-dev python3-pybind11 

Homebrew is recomanded for installing dependencies on Mac OS.

Compiling

Using compile.sh:

./compile.sh

Using cmake:

mkdir build
cmake -B build ./ -DCMAKE_BUILD_TYPE=Release
make -C build -j

Run the start kit

Running the start-kit using commands:

./build/lifelong --inputFile the_input_file_name -o output_file_location

for example:

./build/lifelong --inputFile ./example_problems/random.domain/random_32_32_20_100.json -o test.json

more info on help:

./build/lifelong --help

Windows users

If you are a Windows user, the most straightforward method to utilize our start-kits is by employing the WSL (Windows Subsystem for Linux) subsystem. Follow these steps:

1. Install WSL, please refer to https://learn.microsoft.com/en-us/windows/wsl/install
2. Open a shell in WSL and execute the following commands to install the necessary tools (CMake, GCC, Boost, pip, Pybind11):

sudo apt-get update
sudo apt-get install cmake g++ libboost-all-dev python3-dev python3-pip
pip install pybind11-global numpy

3. Employ the commands provided above to compile the start-kit.

While it's technically possible to use our start-kit with Cygwin, Mingw, and MSVC, doing so would be more complex compared to using WSL. You would likely need to configure the environment yourself.

If you are a docker user, another choice is to develop and test your python implementation under a docker environment. You can the re-create the evaluation environment locally on your machine. For more details, check out the Test in Docker section.

Upgrade Your Start-Kit

If your private start-kit copy repo was created before a start-kit upgrade, you could run the script ./upgrade_start_kit.sh to upgrade your start-kit to the latest version.

You can check version.txt to know the current version of your start-kit.

The upgrade_start_kit.sh will check which file is marked as an upgrade needed and pull those files from the start-kit. It will pull and stage the files, but not commit them. This allows you to review the changes before committing them.

For files stated as unmodifiable in Parepare_Your_Planner.md, you always commit their changes.

⚠️ But please be aware that, the start-kit v2.1.0 introduces requested API changes on task_pool. This requires minor revision to your implementation to adapt to the new API.
This change also impacts the implementation of function update_goal_locations in src/Entry.cpp, therefore, the upgrade script will pull the new version of src/Entry.cpp and may overwrite your changes. You could compare the difference using git diff and decide whether to revert some modifications or partially accept changes on this file.

The upgrade script will not touch most of the participants' implementation file. How every the example implementation in python/pyMAPFPlanner.py,python/pyTaskScheduler.py, inc/MAPFPlanner.h, inc/TaskScheduler.h, src/MAPFPlanner.cpp, src/TaskScheduler.cpp, default_planner/planner.cpp and default_planner/scheduler.cpp are updated with with new API and additional documentaion. You may want to view changes on these files.

Input output description

Please refer to the Input_Output_Format.md.

Prepare Your Planner

Please refer to the Prepare_Your_Submission.md.

Debug and Visualise Your Planner

We provide a visualisation tool written in Python: https://github.com/MAPF-Competition/PlanViz. It is able to visualise the output of the start-kit program and help participants debug the implementations.

Please refer to the project website for more information. Also the document Debug_and_Visualise_Your_Planner which provides helpful hints for interpreting and diagnosing planner output.

Submission Instruction

Please refer to the Submission_Instruction.md.