Sniffbots to the Rescue – Fog Services for a Gas-Sniffing Immersive Robot Collective
Assmann U, Belov M, Thanh-Tien Tenh Cong , Dargie W, Wen J, Urbas L, Lohse C, Panes-Ruiz LA, Riemenschneider L, Ibarlucea B, Cuniberti G, Al Chawa MM, Grossmann C, Ihlenfeld S, Tetzlaff R, Pertuz SA, Goehringer D (2022)
Publication Type: Conference contribution
Publication year: 2022
Journal
Publisher: Springer Science and Business Media Deutschland GmbH
Book Volume: 13226 LNCS
Pages Range: 3-28
Conference Proceedings Title: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Event location: Wittenberg, DEU
ISBN: 9783031047176
DOI: 10.1007/978-3-031-04718-3_1
Abstract
Gas accidents frequently turn industrial or civil structures into extremely dangerous environments. Disasters like the Ahrtal flood in summer 2021 destroy infrastructures such as the gas grid and the power grid, so that people loose control and suddenly find themselves confronted with explosions, suffocation, and death. This paper presents a case study of a robot collective identifying gas leaks with a gas-sniffing wireless sensor network, while providing immersive inspection and tele-operation in the dangerous areas. So-called Sniffbots work in a minimal communication infrastructure, construct world maps autonomously, use them to find gas leaks, remotely inspect, and attempt to close them. To this end, the fog of a Sniffbot should offer services, such as sniff-sensor data aggregation, calculation of points of interest in 2-D and 3-D, virtual reality immersion, remote gripping, as well as autonomous control of flying and driving. While this paper discusses a prototype system still under development, the experiments show the fantastic capabilities of modern gas-sniffing sensors in an immersive robotic fog. Sniffbots, though, at this moment in time, being very expensive robot collectives, will be a very valuable aid in the future to save the life of people in gas disasters.
Involved external institutions
Germany (DE)How to cite
APA:
Assmann, U., Belov, M., Thanh-Tien Tenh Cong, ., Dargie, W., Wen, J., Urbas, L.,... Goehringer, D. (2022). Sniffbots to the Rescue – Fog Services for a Gas-Sniffing Immersive Robot Collective. In Fabrizio Montesi, George Angelos Papadopoulos, Wolf Zimmermann (Eds.), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (pp. 3-28). Wittenberg, DEU: Springer Science and Business Media Deutschland GmbH.
MLA:
Assmann, Uwe, et al. "Sniffbots to the Rescue – Fog Services for a Gas-Sniffing Immersive Robot Collective." Proceedings of the 9th IFIP WG 6.12 European Conference on Service-Oriented and Cloud Computing, ESOCC 2022, Wittenberg, DEU Ed. Fabrizio Montesi, George Angelos Papadopoulos, Wolf Zimmermann, Springer Science and Business Media Deutschland GmbH, 2022. 3-28.
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