TY - GEN
T1 - Sniffbots to the Rescue – Fog Services for a Gas-Sniffing Immersive Robot Collective
AU - Aßmann, Uwe
AU - Belov, Mikhail
AU - Cong, Thanh Tien Tenh
AU - Dargie, Waltenegus
AU - Wen, Jianjun
AU - Urbas, Leon
AU - Lohse, Candy
AU - Panes-Ruiz, Luis Antonio A.
AU - Riemenschneider, Leif
AU - Ibarlucea, Bergoi
AU - Cuniberti, Gianaurelio
AU - Al Chawa, Mohamad Moner
AU - Grossmann, Christoph
AU - Ihlenfeld, Steffen
AU - Tetzlaff, Ronald
AU - Pertuz, Sergio A A.
AU - Goehringer, Diana
N1 - Publisher Copyright:
© 2022, IFIP International Federation for Information Processing.
PY - 2022
Y1 - 2022
N2 - 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.
AB - 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.
KW - Cyber physical systems
KW - UAV
KW - gas sensors
KW - immersion
KW - robotics
KW - tele-operation
KW - wireless sensor networks
UR - https://www.scopus.com/pages/publications/85128953846
U2 - 10.1007/978-3-031-04718-3_1
DO - 10.1007/978-3-031-04718-3_1
M3 - Conference contribution
AN - SCOPUS:85128953846
SN - 9783031047176
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 3
EP - 28
BT - Service-Oriented and Cloud Computing - 9th IFIP WG 6.12 European Conference, ESOCC 2022, Proceedings
A2 - Montesi, Fabrizio
A2 - Papadopoulos, George Angelos
A2 - Zimmermann, Wolf
PB - Springer Science and Business Media Deutschland GmbH
T2 - 9th IFIP WG 6.12 European Conference on Service-Oriented and Cloud Computing, ESOCC 2022
Y2 - 22 March 2022 through 24 March 2022
ER -