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Cooperative N-Boundary Tracking in Large Scale Environments

Euler, Juliane ; Horn, Andreas ; Haumann, Dominik ; Adamy, Jürgen ; Stryk, Oskar von (2012)
Cooperative N-Boundary Tracking in Large Scale Environments.
Proceedings of the IEEE 9th International Conference on Mobile Adhoc and Sensor Systems (MASS). Las Vegas, Nevada, USA (08.10.2012-11.10.2012)
doi: 10.1109/MASS.2012.6708518
Konferenzveröffentlichung, Bibliographie

Kurzbeschreibung (Abstract)

Monitoring in large scale environments is a typ-ical mission in cooperative robotics. This task requires the exploration of a huge domain by a generally small number of sensor equipped mobile robots. As time restrictions prohibit an exhaustive global search, a sampling strategy is required that allows an efficient spatial mapping of the environment. This paper proposes an adaptive sampling strategy for efficient simultaneous tracking of multiple concentration levels of an atmospheric plume by a team of cooperating unmanned aerial vehicles (UAVs). The approach combines uncertainty and correlation-based concentration estimates to generate sampling points based on already gathered data. The adaptive generation of sampling locations is coupled to a distributed model-predictive controller for planning optimal vehicle trajectories under collision and communication constraints. Simulation results demonstrate that connectivity of all involved vehicles can be maintained and an accurate reconstruction of the plume is obtained efficiently.

Typ des Eintrags: Konferenzveröffentlichung
Erschienen: 2012
Autor(en): Euler, Juliane ; Horn, Andreas ; Haumann, Dominik ; Adamy, Jürgen ; Stryk, Oskar von
Art des Eintrags: Bibliographie
Titel: Cooperative N-Boundary Tracking in Large Scale Environments
Sprache: Englisch
Publikationsjahr: 8 Oktober 2012
Ort: Piscataway, NJ, USA
Band einer Reihe: Supplement
Veranstaltungstitel: Proceedings of the IEEE 9th International Conference on Mobile Adhoc and Sensor Systems (MASS)
Veranstaltungsort: Las Vegas, Nevada, USA
Veranstaltungsdatum: 08.10.2012-11.10.2012
DOI: 10.1109/MASS.2012.6708518
URL / URN: http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6...
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Kurzbeschreibung (Abstract):

Monitoring in large scale environments is a typ-ical mission in cooperative robotics. This task requires the exploration of a huge domain by a generally small number of sensor equipped mobile robots. As time restrictions prohibit an exhaustive global search, a sampling strategy is required that allows an efficient spatial mapping of the environment. This paper proposes an adaptive sampling strategy for efficient simultaneous tracking of multiple concentration levels of an atmospheric plume by a team of cooperating unmanned aerial vehicles (UAVs). The approach combines uncertainty and correlation-based concentration estimates to generate sampling points based on already gathered data. The adaptive generation of sampling locations is coupled to a distributed model-predictive controller for planning optimal vehicle trajectories under collision and communication constraints. Simulation results demonstrate that connectivity of all involved vehicles can be maintained and an accurate reconstruction of the plume is obtained efficiently.

Freie Schlagworte: adaptive sampling,boundary tracking,cooperative control,large scale environments
Fachbereich(e)/-gebiet(e): 18 Fachbereich Elektrotechnik und Informationstechnik
18 Fachbereich Elektrotechnik und Informationstechnik > Institut für Automatisierungstechnik und Mechatronik
18 Fachbereich Elektrotechnik und Informationstechnik > Institut für Automatisierungstechnik und Mechatronik > Regelungstechnik und Mechatronik
18 Fachbereich Elektrotechnik und Informationstechnik > Institut für Automatisierungstechnik und Mechatronik > Regelungsmethoden und Robotik (ab 01.08.2022 umbenannt in Regelungsmethoden und Intelligente Systeme)
20 Fachbereich Informatik
20 Fachbereich Informatik > Simulation, Systemoptimierung und Robotik
Hinterlegungsdatum: 20 Dez 2018 07:36
Letzte Änderung: 08 Mai 2019 10:15
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