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.-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 |
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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.-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 LOEWE 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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