Frontier Shepherding: A Bio-Mimetic Multi-robot Framework for Large-Scale Exploration
<|reference_start|>Frontier Shepherding: A Bio-Mimetic Multi-robot Framework for Large-Scale Exploration: Efficient exploration of large-scale environments remains a critical challenge in robotics, with applications ranging from environmental monitoring to search and rescue operations. This article proposes a bio-mimetic multi-robot framework, \textit{Frontier Shepherding (FroShe)}, for large-scale exploration. The presented bio-inspired framework heuristically models frontier exploration similar to the shepherding behavior of herding dogs. This is achieved by modeling frontiers as a sheep swarm reacting to robots modeled as shepherding dogs. The framework is robust across varying environment sizes and obstacle densities and can be easily deployed across multiple agents. Simulation results showcase that the proposed method consistently performed irrespective of the simulated environment's varying sizes and obstacle densities. With the increase in the number of agents, the proposed method outperforms other state-of-the-art exploration methods, with an average improvement of $20\%$ with the next-best approach(for $3$ UAVs). The proposed technique was implemented and tested in a single and dual drone scenario in a real-world forest-like environment.<|reference_end|>
@article{lewis2024frontier,
    title={Frontier Shepherding: A Bio-Mimetic Multi-robot Framework for
  Large-Scale Exploration},
    author={John Lewis, Meysam Basiri, and Pedro U. Lima},
    journal={arXiv preprint arXiv:2409.10931},
    year={2024},
    archivePrefix={arXiv},
    eprint={2409.10931},
    primaryClass={cs.RO}
}