Frontier Shepherding: A Bio-inspired Multi-robot Framework for Large-Scale Exploration
September 17, 2024 Β· Declared Dead Β· π IEEE/RJS International Conference on Intelligent RObots and Systems
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Authors
John Lewis, Meysam Basiri, Pedro U. Lima
arXiv ID
2409.10931
Category
cs.RO: Robotics
Citations
0
Venue
IEEE/RJS International Conference on Intelligent RObots and Systems
Last Checked
6 months ago
Abstract
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.
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