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Arain, Muhammad AsifORCID iD iconorcid.org/0000-0002-5973-7424
Publications (10 of 10) Show all publications
Arain, M. A., Hernandez Bennetts, V., Schaffernicht, E. & Lilienthal, A. (2021). Sniffing out fugitive methane emissions: autonomous remote gas inspection with a mobile robot. The international journal of robotics research, 40(4-5), 782-814
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
Arain, M. A. (2020). Efficient Remote Gas Inspection with an Autonomous Mobile Robot. (Doctoral dissertation). Örebro: Örebro University
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
Fan, H., Arain, M. A., Hernandez Bennetts, V., Schaffernicht, E. & Lilienthal, A. J. (2017). Improving Gas Dispersal Simulation For Mobile Robot Olfaction: Using Robot-Created Occupancy Maps And Remote Gas Sensors In The Simulation Loop. In: 2017 ISOCS/IEEE International Symposium on Olfaction andElectronic Nose (ISOEN 2017) Proceedings: . Paper presented at 2017 ISOCS/IEEE International Symposium on Olfaction and Electronic Nose (ISOEN) 28-31 May 2017 Montreal, QC, Canada. IEEE conference proceedings, Article ID 17013581.
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
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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
Arain, M. A., Fan, H., Hernandez Bennetts, V., Schaffernicht, E. & Lilienthal, A. J. (2017). Improving Gas Tomography With Mobile Robots: An Evaluation of Sensing Geometries in Complex Environments. In: 2017 ISOCS/IEEE International Symposium on Olfaction andElectronic Nose (ISOEN 2017) Proceedings: . Paper presented at 2017 ISOCS/IEEE International Symposium on Olfaction and Electronic Nose (ISOEN) 28-31 May 2017 Montreal QC, Canada. IEEE, Article ID 7968895.
Open this publication in new window or tab >>Improving Gas Tomography With Mobile Robots: An Evaluation of Sensing Geometries in Complex Environments
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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
Arain, M. A., Schaffernicht, E., Hernandez Bennetts, V. & Lilienthal, A. J. (2016). The Right Direction to Smell: Efficient Sensor Planning Strategies for Robot Assisted Gas Tomography. In: 2016 IEEE International Conference on Robotics and Automation (ICRA): . Paper presented at IEEE International Conference on Robotics and Automation (ICRA), Stockholm, Sweden, May 16-21, 2016 (pp. 4275-4281). New York, USA: IEEE Robotics and Automation Society
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
Arain, M. A., Cirillo, M., Hernandez Bennetts, V., Schaffernicht, E., Trincavelli, M. & Lilienthal, A. J. (2015). Efficient Measurement Planning for Remote Gas Sensing with Mobile Robots. In: 2015 IEEE International Conference on Robotics and Automation (ICRA): . Paper presented at 2015 IEEE International Conference on Robotics and Automation (ICRA), Seattle, Washington, USA, May 26-30, 2015 (pp. 3428-3434). Washington, USA: IEEE
Open this publication in new window or tab >>Efficient Measurement Planning for Remote Gas Sensing with Mobile Robots
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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
Arain, M. A., Trincavelli, M., Cirillo, M., Schaffernicht, E. & Lilienthal, A. J. (2015). Global coverage measurement planning strategies for mobile robots equipped with a remote gas sensor. Sensors, 15(3), 6845-6871
Open this publication in new window or tab >>Global coverage measurement planning strategies for mobile robots equipped with a remote gas sensor
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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
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
Arain, M. A., Havoutis, I., Semini, C., Buchli, J. & Caldwell, D. G. (2013). A comparison of search-based planners for a legged robot. In: : . Paper presented at 9th International Workshop on Robot Motion and Control (RoMoCo), Wasowo, Poland, July 3-5, 2013 (pp. 104-109). IEEE
Open this publication in new window or tab >>A comparison of search-based planners for a legged robot
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2013 (English)Conference paper, Published paper (Refereed)
Abstract [en]

Path planning for multi-DoF legged robots is achallenging task due to the high dimensionality and complexityof the planning space. We present our first attempt to builda path planning framework for the hydraulic quadruped -HyQ. Our approach adopts a similar strategy to [1], whereplanning is divided into a task-space and a joint-space part.The task-space planner finds a path for the center of gravity(COG) of the robot, while then the footstep planner generates theappropriate footholds under reachability and stability criteria.Next the joint-space planner translates the task-space COGtrajectories into robot joint angles. We present a comparisonof a set of search-based planning algorithms; Dijkstra, A* andARA*, and evaluate these over a set of given terrains and anumber of varying start and end points. All test runs supportthat our approach is a simple yet robust solution. We reportcomparisons in path length, computation time, and path cost,between the aforementioned planning algorithms.

Place, publisher, year, edition, pages
IEEE, 2013
Keywords
Quadruped Locomotion, Path Planning, Search Algorithms
National Category
Computer Systems
Research subject
Computer Science
Identifiers
urn:nbn:se:oru:diva-30823 (URN)10.1109/RoMoCo.2013.6614593 (DOI)000335775300019 ()2-s2.0-84887302523 (Scopus ID)978-1-4673-5511-7 (ISBN)
Conference
9th International Workshop on Robot Motion and Control (RoMoCo), Wasowo, Poland, July 3-5, 2013
Available from: 2013-09-16 Created: 2013-09-16 Last updated: 2018-05-21Bibliographically approved
Arain, M. A. (2006). Navobot formula 2: a navigation and handling implementation. In: : . Paper presented at IEEEP International Symposium 2006, Karachi, Pakistan.
Open this publication in new window or tab >>Navobot formula 2: a navigation and handling implementation
2006 (English)Conference paper, Published paper (Refereed)
National Category
Robotics
Research subject
Computer Science
Identifiers
urn:nbn:se:oru:diva-28936 (URN)
Conference
IEEEP International Symposium 2006, Karachi, Pakistan
Available from: 2013-05-03 Created: 2013-05-03 Last updated: 2024-01-02Bibliographically approved
Arain, M. A., Ansari, M. A., Khatri, C. K., Maheshwari, B. K. & Kazi, S. A. (2005). Design, Mathematical Modeling & Simulation of a Robot System with 3-DOF. In: : . Paper presented at Technical Exposition 2005, IEEEP Student Symposium, Karachi , Pakistan.
Open this publication in new window or tab >>Design, Mathematical Modeling & Simulation of a Robot System with 3-DOF
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2005 (English)Conference paper, Published paper (Refereed)
National Category
Robotics
Research subject
Electronics
Identifiers
urn:nbn:se:oru:diva-28935 (URN)
Conference
Technical Exposition 2005, IEEEP Student Symposium, Karachi , Pakistan
Available from: 2013-05-03 Created: 2013-05-03 Last updated: 2024-01-02Bibliographically approved
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ORCID iD: ORCID iD iconorcid.org/0000-0002-5973-7424

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