Achim J. Lilienthal is professor of Computer Science and head of the Mobile Robotics and Olfaction (MRO) Lab at Örebro University. His core research interests are in perception systems in unconstrained, dynamic environments. Typically based on approaches that leverage domain knowledge and Artificial Intelligence his research work addresses mobile robot olfaction, rich 3D perception, navigation of autonomous transport robots, human robot interaction and mathematics education research. Achim J. Lilienthal obtained his Ph.D. in computer science from Tübingen University. The Ph.D. thesis addresses gas distribution mapping and gas source localisation with mobile robots. He is author/coauthor of more than 250 refereed conference papers and journal articles.
This paper addresses the problem of localising a static gas source in an uncontrolled indoor envi... more This paper addresses the problem of localising a static gas source in an uncontrolled indoor environment by a mobile robot. In contrast to previous works, especially the condition of an environment that is not artificially ventilated to pro- duce a strong unidirectional airflow is considered. Here, the propagation of the analyte molecules is dominated by turbulence and convection flow rather
Due to its environmental, economical and safety implications, methane leak detection is a crucial... more Due to its environmental, economical and safety implications, methane leak detection is a crucial task to address in the biogas production industry. In this paper, we introduce Gasbot, a robotic platform that aims to automatize methane emission monitoring in landfills and biogas production sites. The distinctive characteristic of the Gasbot platform is the use of a Tunable Laser Absorption Spectroscopy (TDLAS) sensor, along with a novel gas distribution algorithm to generate methane concentration maps of indoor and outdoor exploration areas. The Gasbot platform has been tested in two different scenarios: an underground corridor, where a pipeline leak was simulated and in a decommissioned landfill site, where an artificial methane emission source was introduced.
This paper addresses the problem of localising a static gas source in an uncontrolled indoor envi... more This paper addresses the problem of localising a static gas source in an uncontrolled indoor environment by a mobile robot. In contrast to previous works, especially the condition of an environment that is not artificially ventilated to pro- duce a strong unidirectional airflow is considered. Here, the propagation of the analyte molecules is dominated by turbulence and convection flow rather
Due to its environmental, economical and safety implications, methane leak detection is a crucial... more Due to its environmental, economical and safety implications, methane leak detection is a crucial task to address in the biogas production industry. In this paper, we introduce Gasbot, a robotic platform that aims to automatize methane emission monitoring in landfills and biogas production sites. The distinctive characteristic of the Gasbot platform is the use of a Tunable Laser Absorption Spectroscopy (TDLAS) sensor, along with a novel gas distribution algorithm to generate methane concentration maps of indoor and outdoor exploration areas. The Gasbot platform has been tested in two different scenarios: an underground corridor, where a pipeline leak was simulated and in a decommissioned landfill site, where an artificial methane emission source was introduced.
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Papers by Achim J. Lilienthal