• Corpus ID: 234763080

Graph Neural Networks for Decentralized Multi-Robot Submodular Action Selection

@article{Zhou2021GraphNN,
  title={Graph Neural Networks for Decentralized Multi-Robot Submodular Action Selection},
  author={Lifeng Zhou and Vishnu Dutt Sharma and Qingbiao Li and Amanda Prorok and Alejandro Ribeiro and Vijay R. Kumar},
  journal={ArXiv},
  year={2021},
  volume={abs/2105.08601}
}
In this paper, we develop a learning-based approach for decentralized submodular maximization. We focus on applications where robots are required to jointly select actions, e.g., motion primitives, to maximize team submodular objectives with local communications only. Such applications are essential for large-scale multi-robot coordination such as multi-robot motion planning for area coverage, environment exploration, and target tracking. But the current decentralized submodular maximization… 

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