SniffySquad: Patchiness-Aware Gas Source Localization with Multi-Robot Collaboration

TL;DR

SniffySquad is a multi-robot system that improves gas source localization by addressing patchy gas distributions through active sensing and collaborative strategies, significantly enhancing success rates and efficiency in real-world environments.

Contribution

It introduces a patchiness-aware active sensing and collaborative role adaptation approach, advancing multi-robot gas source localization in complex real-world conditions.

Findings

Success rate increased by over 20%

Path efficiency improved by over 30%

Outperforms existing state-of-the-art solutions

Abstract

Gas source localization is pivotal for the rapid mitigation of gas leakage disasters, where mobile robots emerge as a promising solution. However, existing methods predominantly schedule robots' movements based on reactive stimuli or simplified gas plume models. These approaches typically excel in idealized, simulated environments but fall short in real-world gas environments characterized by their patchy distribution. In this work, we introduce SniffySquad, a multi-robot olfaction-based system designed to address the inherent patchiness in gas source localization. SniffySquad incorporates a patchiness-aware active sensing approach that enhances the quality of data collection and estimation. Moreover, it features an innovative collaborative role adaptation strategy to boost the efficiency of source-seeking endeavors. Extensive evaluations demonstrate that our system achieves an increase in the success rate by $20\%+$ and an improvement in path efficiency by $30\%+$, outperforming state-of-the-art gas source localization solutions.