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Global coverage measurement planning strategies for mobile robots equipped with a remote gas sensor
Örebro University, School of Science and Technology. (Mobile Robotics & Olfaction (MRO) Lab, Center of Applied Autonomous Sensor Systems (AASS))ORCID iD: 0000-0002-5973-7424
Örebro University, School of Science and Technology. (Mobile Robotics & Olfaction (MRO) Lab, Center of Applied Autonomous Sensor Systems (AASS))ORCID iD: 0000-0003-0195-2102
Örebro University, School of Science and Technology. (Mobile Robotics & Olfaction (MRO) Lab, Center of Applied Autonomous Sensor Systems (AASS))
Örebro University, School of Science and Technology. (Mobile Robotics & Olfaction (MRO) Lab, Center of Applied Autonomous Sensor Systems (AASS))ORCID iD: 0000-0002-0804-8637
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2015 (English)In: Sensors, E-ISSN 1424-8220, Vol. 15, no 3, p. 6845-6871Article in journal (Refereed) Published
Abstract [en]

The problem of gas detection is relevant to many real-world applications, such as leak detection in industrial settings and landfill monitoring. In this paper, we address the problem of gas detection in large areas with a mobile robotic platform equipped with a remote gas sensor. We propose an algorithm that leverages a novel method based on convex relaxation for quickly solving sensor placement problems, and for generating an efficient exploration plan for the robot. To demonstrate the applicability of our method to real-world environments, we performed a large number of experimental trials, both on randomly generated maps and on the map of a real environment. Our approach proves to be highly efficient in terms of computational requirements and to provide nearly-optimal solutions.

Place, publisher, year, edition, pages
Basel, Switzerland: MDPI, 2015. Vol. 15, no 3, p. 6845-6871
Keywords [en]
Coverage planning, Mobile robot olfaction, Remote gas detection, Sensor planning, Surveillance robots
National Category
Computer Sciences
Research subject
Computer Science
Identifiers
URN: urn:nbn:se:oru:diva-44407DOI: 10.3390/s150306845ISI: 000354160900112PubMedID: 25803707Scopus ID: 2-s2.0-84928681961OAI: oai:DiVA.org:oru-44407DiVA, id: diva2:807075
Available from: 2015-04-22 Created: 2015-04-22 Last updated: 2024-01-03Bibliographically approved
In thesis
1. Efficient Remote Gas Inspection with an Autonomous Mobile Robot
Open this publication in new window or tab >>Efficient Remote Gas Inspection with an Autonomous Mobile Robot
2020 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Human-caused greenhouse gas emissions are one of the major sources of global warming, which is threatening to reach a tipping point. Inspection systems that can provide direct information about critical factors causing global warming, such as systems for gas detection and location of gas sources, are urgently needed to analyze the fugitive emissions and take necessary actions.

This thesis presents an autonomous robotic system capable of performing efficient exploration by selecting informative sampling positions for gas detection and gas distribution mapping – the Autonomous Remote Methane Explorer (ARMEx). In the design choice of ARMEx, a ground robot carries a spectroscopybased remote gas sensor, such as a Remote Methane Leak Detector (RMLD), that collects integral gas measurements along up to 30 m long optical-beams. The sensor is actuated to sample a large area inside an adjustable field of view, and with the mobility of the robot, adaptive sampling for high spatial resolution in the areas of interest is made possible to inspect large environments.

In a typical gas sampling mission, the robot needs to localize itself and plan a traveling path to visit different locations in the area, which is a largely solved problem. However, the state-of-the-art prior to this thesis fell short of providing the capability to select informative sampling positions autonomously. This thesis introduces efficient measurement strategies to bring autonomy to mobile remote gas sensing. The strategies are based on sensor planning algorithms that minimize the number of measurements and distance traveled while optimizing the inspection criteria: full sensing coverage of the area for gas detection, and suitably overlapping sensing coverage of different viewpoints around areas of interest for gas distribution mapping.

A prototype implementation of ARMEx was deployed in a large, real-world environment where inspection missions performed by the autonomous system were compared with runs teleoperated by human experts. In six experimental trials, the autonomous system created better gas maps, located more gas sources correctly, and provided better sensing coverage with fewer sensing positions than human experts.

Place, publisher, year, edition, pages
Örebro: Örebro University, 2020. p. 78
Series
Örebro Studies in Technology, ISSN 1650-8580 ; 88
Keywords
environmental monitoring, measurement planning, remote gas sensing, mobile robot olfaction, service robots
National Category
Computer Sciences
Identifiers
urn:nbn:se:oru:diva-87393 (URN)978-91-7529-344-8 (ISBN)
Public defence
2020-12-18, Örebro universitet, Forumhuset, Hörsal F, Fakultetsgatan 1, Örebro, 14:00 (English)
Opponent
Supervisors
Available from: 2020-11-16 Created: 2020-11-16 Last updated: 2024-01-03Bibliographically approved

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Arain, Muhammad AsifTrincavelli, MarcoCirillo, MarcelloSchaffernicht, ErikLilienthal, Achim J.

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