libMultiRobotPlanning facilitates task and path planning for systems involving multiple robots or agents. This library offers a collection of search algorithms, including variations of A*, Conflict-Based Search (CBS), and assignment algorithms. The library is primarily written in C++ with a focus on performance through extensive templating. It addresses the challenge of coordinating movements and tasks among multiple robots to achieve a common goal.
The library offers a comprehensive set of algorithms specifically designed for multi-robot coordination, including advanced conflict resolution techniques. It's highly templated, enabling efficient execution across various robot configurations and problem sizes. Examples and documentation are provided to facilitate quick integration and experimentation.
- Single-Robot Algorithms: Implements A*, A* epsilon, and SIPP for individual robot navigation.
- Multi-Robot Algorithms: Includes CBS, ECBS, CBS-TA, and ECBS-TA for coordinated task and path planning.
- Assignment Algorithms: Provides solutions for optimal task allocation among robots.
- C++14: Leverages modern C++ features for performance and code clarity.
- Example Instances: Offers executable examples for demonstrating algorithm usage.
- Unit Tests: Includes unit tests for verifying algorithm correctness.
- Doxygen Documentation: Provides comprehensive documentation for all functions and classes.
The project has been actively developed since 2017 and has a consistent release history with recent commits. The documentation is reasonably complete, and the community, while small, is responsive. The presence of unit tests indicates a commitment to code quality and reliability.
libMultiRobotPlanning is beneficial for researchers and developers working on multi-robot systems, robotics simulations, and automated task allocation problems. It provides a robust set of planning algorithms, reducing development time and simplifying the implementation of complex robotic behaviors. It offers an alternative to developing these algorithms from scratch or relying on less customizable solutions.