{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,8]],"date-time":"2026-03-08T05:37:27Z","timestamp":1772948247642,"version":"3.50.1"},"reference-count":68,"publisher":"Association for Computing Machinery (ACM)","issue":"2","content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":["ACM Trans. Sen. Netw."],"published-print":{"date-parts":[[2026,3,31]]},"abstract":"<jats:p>\n                    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\u2019 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\n                    <jats:italic toggle=\"yes\">SniffySquad<\/jats:italic>\n                    , a multi-robot olfaction-based system designed to address the inherent patchiness in gas source localization.\n                    <jats:italic toggle=\"yes\">SniffySquad<\/jats:italic>\n                    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\n                    <jats:inline-formula content-type=\"math\/tex\">\n                      <jats:tex-math notation=\"LaTeX\" version=\"MathJax\">\\(20\\%+\\)<\/jats:tex-math>\n                    <\/jats:inline-formula>\n                    and an improvement in path efficiency by\n                    <jats:inline-formula content-type=\"math\/tex\">\n                      <jats:tex-math notation=\"LaTeX\" version=\"MathJax\">\\(30\\%+\\)<\/jats:tex-math>\n                    <\/jats:inline-formula>\n                    , outperforming state-of-the-art gas source localization solutions.\n                  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