Frontier Shepherding: A Bio-inspired Multi-robot Framework for Large-Scale Exploration

Fuente: arXiv
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Autores principales: Lewis, John, Basiri, Meysam, Lima, Pedro U.
Formato: Preprint
Publicado: 2024
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author Lewis, John
Basiri, Meysam
Lima, Pedro U.
author_facet Lewis, John
Basiri, Meysam
Lima, Pedro U.
contents 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 Frontier Shepherding (FroShe), a bio-inspired multi-robot framework for large-scale exploration. The framework heuristically models frontier exploration based on the shepherding behavior of herding dogs, where frontiers are treated as a swarm of sheep reacting to robots modeled as shepherding dogs. FroShe is robust across varying environment sizes and obstacle densities, requiring minimal parameter tuning for deployment across multiple agents. Simulation results demonstrate that the proposed method performs consistently, regardless of environment complexity, and outperforms state-of-the-art exploration strategies by an average of 20% with three UAVs. The approach was further validated in real-world experiments using single- and dual-drone deployments in a forest-like environment.
format Preprint
id arxiv_https___arxiv_org_abs_2409_10931
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Frontier Shepherding: A Bio-inspired Multi-robot Framework for Large-Scale Exploration
Lewis, John
Basiri, Meysam
Lima, Pedro U.
Robotics
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 Frontier Shepherding (FroShe), a bio-inspired multi-robot framework for large-scale exploration. The framework heuristically models frontier exploration based on the shepherding behavior of herding dogs, where frontiers are treated as a swarm of sheep reacting to robots modeled as shepherding dogs. FroShe is robust across varying environment sizes and obstacle densities, requiring minimal parameter tuning for deployment across multiple agents. Simulation results demonstrate that the proposed method performs consistently, regardless of environment complexity, and outperforms state-of-the-art exploration strategies by an average of 20% with three UAVs. The approach was further validated in real-world experiments using single- and dual-drone deployments in a forest-like environment.
title Frontier Shepherding: A Bio-inspired Multi-robot Framework for Large-Scale Exploration
topic Robotics
url https://arxiv.org/abs/2409.10931