Sniffing out fugitive methane emissions: autonomous remote gas inspection with a mobile robot

• Published in: The International journal of robotics research 2021-04, Vol.40 (4-5), p.782-814
• Main Authors: Arain, Muhammad Asif, Hernandez Bennetts, Victor, Schaffernicht, Erik, Lilienthal, Achim J
• Format: Article
• Language: English
• Subjects: Adaptive systems; Air monitoring; Air pollution; autonomous exploration; Configurations; Environmental monitoring; Field of view; fugitivemethane emissions; Gas sensors; Indoor environments; Inspection; Integrals; Mapping; Methane; mobile robot olfaction; Pollution monitoring; remote gas inspection; Remote sensing; Remote sensors; Robots; Spatial resolution; Tomography
• ISSN: 0278-3649; 1741-3176; 1741-3176
• DOI: 10.1177/0278364920954907

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 “Autonomous Remote Methane Explorer” ( ARMEx ) 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 ARMEx 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.