To Örebro University

oru.seÖrebro University Publications
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Efficient Remote Gas Inspection with an Autonomous Mobile Robot
Örebro University, School of Science and Technology.ORCID iD: 0000-0002-5973-7424
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 [en]
environmental monitoring, measurement planning, remote gas sensing, mobile robot olfaction, service robots
National Category
Computer Sciences
Identifiers
URN: urn:nbn:se:oru:diva-87393ISBN: 978-91-7529-344-8 (print)OAI: oai:DiVA.org:oru-87393DiVA, id: diva2:1501123
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
List of papers
1. Global coverage measurement planning strategies for mobile robots equipped with a remote gas sensor
Open this publication in new window or tab >>Global coverage measurement planning strategies for mobile robots equipped with a remote gas sensor
Show others...
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
Keywords
Coverage planning, Mobile robot olfaction, Remote gas detection, Sensor planning, Surveillance robots
National Category
Computer Sciences
Research subject
Computer Science
Identifiers
urn:nbn:se:oru:diva-44407 (URN)10.3390/s150306845 (DOI)000354160900112 ()25803707 (PubMedID)2-s2.0-84928681961 (Scopus ID)
Available from: 2015-04-22 Created: 2015-04-22 Last updated: 2024-01-03Bibliographically approved
2. Efficient Measurement Planning for Remote Gas Sensing with Mobile Robots
Open this publication in new window or tab >>Efficient Measurement Planning for Remote Gas Sensing with Mobile Robots
Show others...
2015 (English)In: 2015 IEEE International Conference on Robotics and Automation (ICRA), Washington, USA: IEEE, 2015, p. 3428-3434Conference paper, Published paper (Refereed)
Abstract [en]

The problem of gas detection is relevant to manyreal-world applications, such as leak detection in industrialsettings and surveillance. In this paper we address the problemof gas detection in large areas with a mobile robotic platformequipped with a remote gas sensor. We propose a novelmethod based on convex relaxation for quickly finding anexploration plan that guarantees a complete coverage of theenvironment. Our method proves to be highly efficient in termsof computational requirements and to provide nearly-optimalsolutions. We validate our approach both in simulation andin real environments, thus demonstrating its applicability toreal-world problems.

Place, publisher, year, edition, pages
Washington, USA: IEEE, 2015
Keywords
Sensor planning, mobile robot olfaction, remote gas sensing
National Category
Computer Sciences
Research subject
Computer Science
Identifiers
urn:nbn:se:oru:diva-46796 (URN)10.1109/ICRA.2015.7139673 (DOI)000370974903063 ()978-1-4799-6923-4 (ISBN)
Conference
2015 IEEE International Conference on Robotics and Automation (ICRA), Seattle, Washington, USA, May 26-30, 2015
Available from: 2015-11-25 Created: 2015-11-25 Last updated: 2024-01-03Bibliographically approved
3. The Right Direction to Smell: Efficient Sensor Planning Strategies for Robot Assisted Gas Tomography
Open this publication in new window or tab >>The Right Direction to Smell: Efficient Sensor Planning Strategies for Robot Assisted Gas Tomography
2016 (English)In: 2016 IEEE International Conference on Robotics and Automation (ICRA), New York, USA: IEEE Robotics and Automation Society, 2016, p. 4275-4281Conference paper, Published paper (Refereed)
Abstract [en]

Creating an accurate model of gas emissions is an important task in monitoring and surveillance applications. A promising solution for a range of real-world applications are gas-sensitive mobile robots with spectroscopy-based remote sensors that are used to create a tomographic reconstruction of the gas distribution. The quality of these reconstructions depends crucially on the chosen sensing geometry. In this paper we address the problem of sensor planning by investigating sensing geometries that minimize reconstruction errors, and then formulate an optimization algorithm that chooses sensing configurations accordingly. The algorithm decouples sensor planning for single high concentration regions (hotspots) and subsequently fuses the individual solutions to a global solution consisting of sensing poses and the shortest path between them. The proposed algorithm compares favorably to a template matching technique in a simple simulation and in a real-world experiment. In the latter, we also compare the proposed sensor planning strategy to the sensing strategy of a human expert and find indications that the quality of the reconstructed map is higher with the proposed algorithm.

Place, publisher, year, edition, pages
New York, USA: IEEE Robotics and Automation Society, 2016
Keywords
Sensor planning, robot exploration, sensing geometry, robot assisted gas tomography, mobile robot olfaction, coverage planning, surveillance robots
National Category
Robotics Computer Systems
Research subject
Computer Science
Identifiers
urn:nbn:se:oru:diva-50886 (URN)10.1109/ICRA.2016.7487624 (DOI)000389516203101 ()2-s2.0-84977543569 (Scopus ID)
Conference
IEEE International Conference on Robotics and Automation (ICRA), Stockholm, Sweden, May 16-21, 2016
Available from: 2016-06-16 Created: 2016-06-16 Last updated: 2022-08-09Bibliographically approved
4. Improving Gas Tomography With Mobile Robots: An Evaluation of Sensing Geometries in Complex Environments
Open this publication in new window or tab >>Improving Gas Tomography With Mobile Robots: An Evaluation of Sensing Geometries in Complex Environments
Show others...
2017 (English)In: 2017 ISOCS/IEEE International Symposium on Olfaction andElectronic Nose (ISOEN 2017) Proceedings, IEEE, 2017, article id 7968895Conference paper, Published paper (Refereed)
Abstract [en]

An accurate model of gas emissions is of high importance in several real-world applications related to monitoring and surveillance. Gas tomography is a non-intrusive optical method to estimate the spatial distribution of gas concentrations using remote sensors. The choice of sensing geometry, which is the arrangement of sensing positions to perform gas tomography, directly affects the reconstruction quality of the obtained gas distribution maps. In this paper, we present an investigation of criteria that allow to determine suitable sensing geometries for gas tomography. We consider an actuated remote gas sensor installed on a mobile robot, and evaluated a large number of sensing configurations. Experiments in complex settings were conducted using a state-of-the-art CFD-based filament gas dispersal simulator. Our quantitative comparison yields preferred sensing geometries for sensor planning, which allows to better reconstruct gas distributions.

Place, publisher, year, edition, pages
IEEE, 2017
National Category
Computer Sciences Robotics
Identifiers
urn:nbn:se:oru:diva-60646 (URN)10.1109/ISOEN.2017.7968895 (DOI)978-1-5090-2392-9 (ISBN)978-1-5090-2393-6 (ISBN)
Conference
2017 ISOCS/IEEE International Symposium on Olfaction and Electronic Nose (ISOEN) 28-31 May 2017 Montreal QC, Canada
Available from: 2017-09-06 Created: 2017-09-06 Last updated: 2024-01-03Bibliographically approved
5. Improving Gas Dispersal Simulation For Mobile Robot Olfaction: Using Robot-Created Occupancy Maps And Remote Gas Sensors In The Simulation Loop
Open this publication in new window or tab >>Improving Gas Dispersal Simulation For Mobile Robot Olfaction: Using Robot-Created Occupancy Maps And Remote Gas Sensors In The Simulation Loop
Show others...
2017 (English)In: 2017 ISOCS/IEEE International Symposium on Olfaction andElectronic Nose (ISOEN 2017) Proceedings, IEEE conference proceedings, 2017, article id 17013581Conference paper, Published paper (Refereed)
Abstract [en]

Mobile robot platforms equipped with olfaction systems have been used in many gas sensing applications. However, in-field validation of mobile robot olfaction systems is time consuming, expensive, cumbersome and lacks repeatability. In order to address these issues, simulation tools are used. However, the available mobile robot olfaction simulations lack models for remote gas sensors, and the possibility to import geometrical representations of actual real-world environments in a convenient way. In this paper, we describe extensions to an open-source CFD-based filament gas dispersal simulator. These improvements arrow to use robot-created occupancy maps and offer remote sensing capabilities in the simulation loop. We demonstrate the novel features in an example application: we created a 3D map a complex indoor environment, and performed a gas emission monitoring task with a Tunable Diode Laser Absorption Spectroscopy based remote gas sensor in a simulated version of the environment.

Place, publisher, year, edition, pages
IEEE conference proceedings, 2017
National Category
Computer Sciences Robotics
Identifiers
urn:nbn:se:oru:diva-60633 (URN)10.1109/ISOEN.2017.7968874 (DOI)978-1-5090-2392-9 (ISBN)978-1-5090-2393-6 (ISBN)
Conference
2017 ISOCS/IEEE International Symposium on Olfaction and Electronic Nose (ISOEN) 28-31 May 2017 Montreal, QC, Canada
Available from: 2017-09-06 Created: 2017-09-06 Last updated: 2024-01-03Bibliographically approved
6. Sniffing out fugitive methane emissions: autonomous remote gas inspection with a mobile robot
Open this publication in new window or tab >>Sniffing out fugitive methane emissions: autonomous remote gas inspection with a mobile robot
2021 (English)In: The international journal of robotics research, ISSN 0278-3649, E-ISSN 1741-3176, Vol. 40, no 4-5, p. 782-814Article in journal (Refereed) Published
Abstract [en]

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 anARMExprototype 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.

Place, publisher, year, edition, pages
Sage Publications, 2021
Keywords
Environmental monitoring, autonomous exploration, remote gas inspection, mobile robot olfaction, fugitivemethane emissions
National Category
Computer Sciences
Identifiers
urn:nbn:se:oru:diva-87622 (URN)10.1177/0278364920954907 (DOI)000648404100007 ()2-s2.0-85096537707 (Scopus ID)
Funder
EU, Horizon 2020, ICT-23-2014 645101
Note

Funding Agencies:

European Commission ICT-23-2014 645101

SURVEYOR (Vinnova) 2017-05468

project RAISE 20130196

Available from: 2020-11-26 Created: 2020-11-26 Last updated: 2024-01-03Bibliographically approved

Open Access in DiVA

Cover(176 kB)178 downloads
File information
File name FULLTEXT01.pdfFile size 176 kBChecksum SHA-512
0539fc6a3ea4b6a2fa87c6220f28b52f478def567f98aa505e4620325018d66ae55fd06f1aff94c145f02db11c54cf98c2b68113826887d36df8d50ace05f692
Type fulltextMimetype application/pdf
Efficient Remote Gas Inspection with an Autonomous Mobile Robot(74693 kB)146 downloads
File information
File name FULLTEXT02.pdfFile size 74693 kBChecksum SHA-512
c912ecafd28d90e4026534d395c7a2d9c8630dc96158e75d865867bea8db7cfe0e950a8686b5de113de7ec7f9bc6c6e1a3a88b15a8d7c5edcc1bd2836f165605
Type fulltextMimetype application/pdf
Spikblad(165 kB)52 downloads
File information
File name SPIKBLAD01.pdfFile size 165 kBChecksum SHA-512
e7492261ae0454f09db48d6665caac92adbc6d8d0c397d6f2a60ad91759ad057ec40fdbff147cb5b191cfc550ccd1f78b3baff051b5120e427e69c7d65755c71
Type spikbladMimetype application/pdf

Authority records

Arain, Muhammad Asif

Search in DiVA

By author/editor
Arain, Muhammad Asif
By organisation
School of Science and Technology
Computer Sciences

Search outside of DiVA

GoogleGoogle Scholar
Total: 324 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

isbn
urn-nbn

Altmetric score

isbn
urn-nbn
Total: 1544 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf