FRAME: Fast and Robust Autonomous 3D Point Cloud Map-Merging for Egocentric Multi-Robot Exploration

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FRAME is a fast and robust autonomous map-merging framework for multi-agent systems that aims to assist multi-robot exploration missions.

System Architecture

How to Install

Dependencies

How to Use

Parameters

Acknowledgement

Papers:

• 2023 IEEE International Conference on Robotics and Automation (ICRA)
• Accepted in Transactions on Field Robotics (T-FR)

If you found this work useful, please cite as follows:

@INPROCEEDINGS{stathoulopoulos2023frame,  
    author={Stathoulopoulos, Nikolaos and Koval, Anton and Agha-mohammadi, Ali-akbar and Nikolakopoulos, George},
    booktitle={2023 IEEE International Conference on Robotics and Automation (ICRA)},
    title={{FRAME: Fast and Robust Autonomous 3D Point Cloud Map-Merging for Egocentric Multi-Robot Exploration}},
    year={2023},
    volume={},
    number={},
    pages={3483-3489},
    doi={10.1109/ICRA48891.2023.10160771}
}
@ARTICLE{stathoulopoulos2024frame,
  author={Stathoulopoulos, Nikolaos and Lindqvist, Björn and Koval, Anton and Agha-Mohammadi, Ali-Akbar and Nikolakopoulos, George},
  journal={IEEE Transactions on Field Robotics},
  title={{FRAME: A Modular Framework for Autonomous Map Merging: Advancements in the Field}},
  year={2024},
  volume={1},
  number={},
  pages={1-26},
  keywords={Robots;Point cloud compression;Feature extraction;Three-dimensional displays;Robot sensing systems;Robot kinematics;Accuracy;Feature extraction;machine learning;multirobot systems (MRSs);simultaneous localization and mapping (SLAM)},
  doi={10.1109/TFR.2024.3419439}
}