TY - JOUR
T1 - Sniffing out fugitive methane emissions
T2 - autonomous remote gas inspection with a mobile robot
AU - Arain, Muhammad Asif
AU - Hernandez Bennetts, Victor
AU - Schaffernicht, Erik
AU - Lilienthal, Achim J.
N1 - Publisher Copyright:
© The Author(s) 2020.
PY - 2021/4
Y1 - 2021/4
N2 - 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” ((Formula presented.)) 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 presented.) 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.
AB - 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” ((Formula presented.)) 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 presented.) 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.
KW - Environmental monitoring
KW - autonomous exploration
KW - fugitive methane emissions
KW - mobile robot olfaction
KW - remote gas inspection
UR - http://www.scopus.com/inward/record.url?scp=85096537707&partnerID=8YFLogxK
U2 - 10.1177/0278364920954907
DO - 10.1177/0278364920954907
M3 - Article
AN - SCOPUS:85096537707
SN - 0278-3649
VL - 40
SP - 782
EP - 814
JO - International Journal of Robotics Research
JF - International Journal of Robotics Research
IS - 4-5
ER -