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Optimized Vehicle-Specific Trajectories for Cooperative Process Estimation by Sensor-Equipped UAVs

Euler, J. ; Stryk, Oskar von (2017)
Optimized Vehicle-Specific Trajectories for Cooperative Process Estimation by Sensor-Equipped UAVs.
International Conference on Robotics and Automation (ICRA). Singapore (29.05.2017-03.06.2017)
doi: 10.1109/ICRA.2017.7989386
Konferenzveröffentlichung, Bibliographie

Kurzbeschreibung (Abstract)

This paper presents a sequential optimum design approach for estimating the parameters of an atmospheric dispersion process model based on measurement data gathered by a team of cooperating sensor-equipped UAVs. Locally optimal waypoint sequences that account for each UAV’s possibly heterogeneous motion dynamics are computed by minimizing a suitable optimality criterion. Following these waypoints, the UAVs cooperatively maximize the information gain of the acquired measurements. A decentralized data-driven online control scheme is proposed that couples parameter estimation, waypoint calculation, and vehicle control and enables the UAVs to adaptively observe the dynamic process and iteratively improve the parameter estimate. Simulations demonstrate the effectiveness of the proposed scheme in reducing the error between the estimated and the true dispersion model parameters compared to non-adaptive sensing strategies. In addition, the effect of using different optimality criteria, different numbers and types of UAVs as well as two options for decentralizing the waypoint calculation are investigated.

Typ des Eintrags: Konferenzveröffentlichung
Erschienen: 2017
Autor(en): Euler, J. ; Stryk, Oskar von
Art des Eintrags: Bibliographie
Titel: Optimized Vehicle-Specific Trajectories for Cooperative Process Estimation by Sensor-Equipped UAVs
Sprache: Englisch
Publikationsjahr: 27 Juli 2017
Verlag: IEEE
Buchtitel: 2017 IEEE International Conference on Robotics and Automation
Veranstaltungstitel: International Conference on Robotics and Automation (ICRA)
Veranstaltungsort: Singapore
Veranstaltungsdatum: 29.05.2017-03.06.2017
DOI: 10.1109/ICRA.2017.7989386
Kurzbeschreibung (Abstract):

This paper presents a sequential optimum design approach for estimating the parameters of an atmospheric dispersion process model based on measurement data gathered by a team of cooperating sensor-equipped UAVs. Locally optimal waypoint sequences that account for each UAV’s possibly heterogeneous motion dynamics are computed by minimizing a suitable optimality criterion. Following these waypoints, the UAVs cooperatively maximize the information gain of the acquired measurements. A decentralized data-driven online control scheme is proposed that couples parameter estimation, waypoint calculation, and vehicle control and enables the UAVs to adaptively observe the dynamic process and iteratively improve the parameter estimate. Simulations demonstrate the effectiveness of the proposed scheme in reducing the error between the estimated and the true dispersion model parameters compared to non-adaptive sensing strategies. In addition, the effect of using different optimality criteria, different numbers and types of UAVs as well as two options for decentralizing the waypoint calculation are investigated.

Fachbereich(e)/-gebiet(e): 20 Fachbereich Informatik
20 Fachbereich Informatik > Simulation, Systemoptimierung und Robotik
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LOEWE > LOEWE-Schwerpunkte
LOEWE > LOEWE-Schwerpunkte > NICER – Vernetzte infrastrukturlose Kooperation zur Krisenbewältigung
Hinterlegungsdatum: 15 Aug 2017 13:25
Letzte Änderung: 02 Dez 2021 09:36
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