erl_path_planning

erl_path_planning is a C++ library providing a collection of path planning algorithms for robotics applications.

Features

• Multiple Planning Algorithms: A*, AMRA*, Hybrid A*, and more
• LTL Mission Planning: Support for Linear Temporal Logic specifications in 2D and 3D
• Flexible Heuristics: Customizable heuristic functions including LLM-based scene graph heuristics
• Kinodynamic Planning: Dubins paths and Reeds-Shepp curves for car-like robots
• Multi-Resolution Search: AMRA* with anytime multi-resolution capabilities
• Python Bindings: Full Python API for all major algorithms

Available Algorithms

Search-Based Planners

• A*: Classic optimal graph search algorithm
• AMRA*: Anytime Multi-Resolution Multi-Heuristic A* - efficient anytime planning with multiple heuristics and resolutions
• Hybrid A*: Grid-based planner with continuous state space for non-holonomic vehicles

Kinodynamic Planning

• Dubins Path: Shortest path for car-like robots with minimum turning radius (forward only)
• Reeds-Shepp Path: Shortest path for car-like robots with minimum turning radius (forward and backward)

Heuristics

• Heuristic Base: Base class for custom heuristics
• LTL 2D Heuristic: Heuristic for LTL-based planning in 2D environments
• LTL 3D Heuristic: Heuristic for LTL-based planning in 3D environments
• LLM Scene Graph Heuristic: AI-powered heuristic using large language models and scene understanding

Utilities

• Planning Output: Data structures for path and planning results
• Search Planning Interface: Common interface for search-based planners

Getting Started

Prerequisites

• CMake 3.24 or higher
• A C++17 compatible compiler
• Python 3.8+ (for Python bindings)

Create Workspace

mkdir -p <your_workspace>/src && \
vcs import --input https://raw.githubusercontent.com/ExistentialRobotics/erl_path_planning/refs/heads/main/erl_path_planning.repos <your_workspace>/src

Dependencies

• erl_cmake_tools
• erl_common
• erl_env
• erl_geometry
• Spot (optional, for LTL planning)

Install Dependencies

# Ubuntu 20.04
wget -qO - https://raw.githubusercontent.com/ExistentialRobotics/erl_common/refs/heads/main/scripts/setup_ubuntu_20.04.bash | bash
wget -qO - https://raw.githubusercontent.com/ExistentialRobotics/erl_geometry/refs/heads/main/scripts/setup_ubuntu_20.04.bash | bash
wget -qO - https://raw.githubusercontent.com/ExistentialRobotics/erl_env/refs/heads/main/scripts/setup_ubuntu_20.04.bash | bash

# Ubuntu 22.04, 24.04
wget -qO - https://raw.githubusercontent.com/ExistentialRobotics/erl_common/refs/heads/main/scripts/setup_ubuntu_22.04_24.04.bash | bash
wget -qO - https://raw.githubusercontent.com/ExistentialRobotics/erl_geometry/refs/heads/main/scripts/setup_ubuntu_22.04_24.04.bash | bash
wget -qO - https://raw.githubusercontent.com/ExistentialRobotics/erl_env/refs/heads/main/scripts/setup_ubuntu_22.04_24.04.bash | bash

# Arch Linux (for Spot LTL support)
paru -S spot

Docker Option

The easiest way to get started is to use the provided Docker files, which contains all dependencies.

Use as a Standard CMake Package

cd <your_workspace>
touch CMakeLists.txt

Add the following lines to your CMakeLists.txt:

cmake_minimum_required(VERSION 3.16)
project(<your_project_name>)
add_subdirectory(src/erl_cmake_tools)
add_subdirectory(src/erl_common)
add_subdirectory(src/erl_covariance)
add_subdirectory(src/erl_geometry)
add_subdirectory(src/erl_env)
add_subdirectory(src/erl_path_planning)

Then run the following commands:

mkdir -p build
cd build
cmake .. -DCMAKE_BUILD_TYPE=Release
make -j`nproc`

Use as a ROS Package

cd <your_workspace>
source /opt/ros/<distro>/setup.bash
# for ROS1
catkin build erl_path_planning
source devel/setup.bash
# for ROS2
colcon build --packages-up-to erl_path_planning
source install/setup.bash

See also 🚪erl_path_planning_ros for ROS nodes and integration.

Install As Python Package

• Make sure you have installed all dependencies.
• Make sure you have the correct Python environment activated, pipenv is recommended.

cd <your_workspace>
for package in erl_cmake_tools erl_common erl_covariance erl_geometry erl_env erl_path_planning; do
    cd src/$package
    pip install . --verbose --no-build-isolation
    cd ../..
done

Gallery

• AMRA*: Detailed documentation on AMRA* algorithm with visualization examples and benchmarks

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

License

This project is licensed under the MIT License - see the LICENSE file for details.

Citation

If you use this library in your research, please cite:

@software{erl_path_planning,
  author = {Dai, Zhirui and Existential Robotics Lab},
  title = {erl_path_planning: A C++ Path Planning Library},
  url = {https://github.com/ExistentialRobotics/erl_path_planning},
  year = {2025}
}

For AMRA* specifically:

@inproceedings{srivastava2021amra,
  title={AMRA*: Anytime Multi-Resolution Multi-Heuristic A*},
  author={Srivastava, Dhruv and Likhachev, Maxim},
  booktitle={2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)},
  year={2021}
}

Acknowledgments

• AMRA* implementation based on the original work by Dhruv Srivastava
• Dubins and Reeds-Shepp path implementations inspired by classical motion planning literature

Related Projects

• erl_path_planning_ros: ROS1/ROS2 integration for this library
• erl_geometry: Geometry processing library
• erl_env: Environment representation library