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

实时计算 温室气体 甲烷 遥感 计算机科学 环境科学 机器人 模拟 人工智能 地理 地质学 生态学 生物 海洋学
作者
Muhammad Asif Arain,Victor Hernandez Bennetts,Erik Schaffernicht,Achim J. Lilienthal
出处
期刊:The International Journal of Robotics Research [SAGE]
卷期号:40 (4-5): 782-814 被引量:16
标识
DOI:10.1177/0278364920954907
摘要

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: 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.
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