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 (8-11 Oct. 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: | 8-11 Oct. 2012 |
| DOI: | 10.1109/MASS.2012.6708518 |
| URL / URN: | http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6... |
| Zugehörige Links: | |
| 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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