trajallocpy 0.0.14

TrajAllocPy is a Python library that provides functionality for trajectory task Allocaition using Consensus based bundle algorithm

TrajAllocPy: Decentralized multi-robot/agent task allocation for area coverage problems

TrajAllocPy is a Python library that provides functionality for trajectory task allocation based on CBBA (Consensus Based Bundle Algorithm).

Coverage task dataset

This repository uses dataset format given in: https://github.com/kasperg3/CoverageTasks

Installation

The package is regularly updated and new releases are created when significant changes to the main branch has happened.

pip install trajallocpy

Build from source

You can install TrajAllocPy using pip. Simply navigate to your projects root directory and run:

pip install -r requirements.txt
pip install -e .

The "-e" argument for pip is to enable the developer to edit the python source code and perform tests without having to rebuild everything.

Usage

To use TrajAllocPy in your Python project, you can import it as follows:

import TrajAllocPy

You can then use the provided functions and classes to perform trajectory allocaion and task planning based on the consensus based bundle algorithm algorithm. See the examples in exmaples.md

Contributing & Development

Install the bindings in dev mode:

pip install -e .

To contribute to TrajAllocPy, start by forking the repository on GitHub. Create a new branch for your changes, make the necessary code edits, commit your changes with clear messages, and push them to your fork. Create a pull request from your branch to the original repository, describing your changes and addressing any related issues. Once your pull request is approved, a project maintainer will merge it into the main branch.

Citation

If you use TrajAllocPy in your work, please cite the following paper:

@inproceedings{grontved2022icar,
  title={Decentralized Multi-UAV Trajectory Task Allocation in Search and Rescue Applications},
  author={Gr{\o}ntved, Kasper Andreas R{\o}mer and Schultz, Ulrik Pagh and Christensen, Anders Lyhne},
  booktitle={21st International Conference on Advanced Robotics},
  year={2023},
  organization={IEEE}
}

License

This library is released under the MIT License. Feel free to use, modify, and distribute it in your projects.

Issues and Contributions

If you encounter any issues or have ideas for improvements, please open an issue on the GitHub repository. Contributions in the form of pull requests are also welcome.

Support

For support and inquiries, you can contact the maintainers of this library at [e-mail].

Thank you for using TrajAllocPy! We hope it proves to be a valuable tool for your trajectory generation and task planning needs.