{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,11]],"date-time":"2026-05-11T15:38:44Z","timestamp":1778513924576,"version":"3.51.4"},"reference-count":71,"publisher":"SAGE Publications","issue":"4-5","license":[{"start":{"date-parts":[[2020,11,23]],"date-time":"2020-11-23T00:00:00Z","timestamp":1606089600000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Smokebot","award":["ICT-23-2014 645101"],"award-info":[{"award-number":["ICT-23-2014 645101"]}]}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["The International Journal of Robotics Research"],"published-print":{"date-parts":[[2021,4]]},"abstract":"<jats:p>Air pollution causes millions of premature deaths every year, and fugitive emissions of, e.g., methane are major causes of global warming. Correspondingly, air pollution monitoring systems are urgently needed. Mobile, autonomous monitoring can provide adaptive and higher spatial resolution compared with traditional monitoring stations and allows fast deployment and operation in adverse environments. We present a mobile robot solution for autonomous gas detection and gas distribution mapping using remote gas sensing. Our \u201cAutonomous Remote Methane Explorer\u201d ([Formula: see text]) is equipped with an actuated spectroscopy-based remote gas sensor, which collects integral gas measurements along up to 30 m long optical beams. State-of-the-art 3D mapping and robot localization allow the precise location of the optical beams to be determined, which then facilitates gas tomography (tomographic reconstruction of local gas distributions from sets of integral gas measurements). To autonomously obtain informative sampling strategies for gas tomography, we reduce the search space for gas inspection missions by defining a sweep of the remote gas sensor over a selectable field of view as a sensing configuration. We describe two different ways to find sequences of sensing configurations that optimize the criteria for gas detection and gas distribution mapping while minimizing the number of measurements and distance traveled. We evaluated an [Formula: see text] prototype deployed in a large, challenging indoor environment with eight gas sources. In comparison with human experts teleoperating the platform from a distant building, the autonomous strategy produced better gas maps with a lower number of sensing configurations and a slightly longer route.<\/jats:p>","DOI":"10.1177\/0278364920954907","type":"journal-article","created":{"date-parts":[[2020,11,24]],"date-time":"2020-11-24T01:35:15Z","timestamp":1606181715000},"page":"782-814","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":25,"title":["Sniffing out fugitive methane emissions: autonomous remote gas inspection with a mobile robot"],"prefix":"10.1177","volume":"40","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5973-7424","authenticated-orcid":false,"given":"Muhammad Asif","family":"Arain","sequence":"first","affiliation":[{"name":"Mobile Robotics and Olfaction (MRO) Lab, Center for Applied Autonomous Sensor Systems (AASS), School of Science and Technology, \u00d6rebro University, \u00d6rebro, Sweden"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Victor","family":"Hernandez Bennetts","sequence":"additional","affiliation":[{"name":"Mobile Robotics and Olfaction (MRO) Lab, Center for Applied Autonomous Sensor Systems (AASS), School of Science and Technology, \u00d6rebro University, \u00d6rebro, Sweden"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Erik","family":"Schaffernicht","sequence":"additional","affiliation":[{"name":"Mobile Robotics and Olfaction (MRO) Lab, Center for Applied Autonomous Sensor Systems (AASS), School of Science and Technology, \u00d6rebro University, \u00d6rebro, Sweden"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Achim J","family":"Lilienthal","sequence":"additional","affiliation":[{"name":"Mobile Robotics and Olfaction (MRO) Lab, Center for Applied Autonomous Sensor Systems (AASS), School of Science and Technology, \u00d6rebro University, \u00d6rebro, Sweden"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"179","published-online":{"date-parts":[[2020,11,23]]},"reference":[{"key":"bibr1-0278364920954907","doi-asserted-by":"publisher","DOI":"10.1021\/acs.est.5b05059"},{"key":"bibr2-0278364920954907","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.1202407109"},{"key":"bibr3-0278364920954907","volume-title":"The Traveling Salesman Problem: A Computational Study","author":"Applegate DL","year":"2006"},{"key":"bibr4-0278364920954907","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA.2015.7139673"},{"key":"bibr5-0278364920954907","doi-asserted-by":"publisher","DOI":"10.1109\/ISOEN.2017.7968895"},{"key":"bibr6-0278364920954907","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA.2016.7487624"},{"key":"bibr7-0278364920954907","doi-asserted-by":"publisher","DOI":"10.3390\/s150306845"},{"key":"bibr8-0278364920954907","doi-asserted-by":"publisher","DOI":"10.1109\/ROBOT.2009.5152338"},{"key":"bibr9-0278364920954907","doi-asserted-by":"publisher","DOI":"10.1109\/IPSN.2008.28"},{"key":"bibr10-0278364920954907","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA.2013.6630693"},{"key":"bibr11-0278364920954907","doi-asserted-by":"publisher","DOI":"10.1364\/OL.4.000075"},{"key":"bibr12-0278364920954907","doi-asserted-by":"publisher","DOI":"10.3115\/1072064.1072067"},{"key":"bibr13-0278364920954907","unstructured":"Christensen J, Olhoff A (2019) Lessons from a decade of emissions gap assessments. 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