Euler, Juliane (2017)
Optimal Cooperative Control of UAVs for Dynamic Data-Driven Monitoring Tasks.
Technische Universität Darmstadt
Dissertation, Erstveröffentlichung
Kurzbeschreibung (Abstract)
In recent years, there has been an immense improvement of methods and technology for Unmanned Aerial Vehicles (UAVs). By now, a steadily growing number of affordable platforms, as well as accurate onboard sensors, are available, which enables the use of UAVs as a remote sensing tool in various monitoring, surveillance, and disaster response tasks. This thesis deals with the challenging application scenario of monitoring atmospheric dispersion processes using multiple sensor-equipped UAVs. The idea is to enable the UAVs to autonomously move through the domain such that the utility of measurements taken along the way is maximized and cooperation among the team members is exploited. A three-part solution to this problem is developed. For cooperative control of multiple vehicles, a decentralized model-predictive control approach is proposed that is based on a mixed-integer linear system description. As data-driven adaptive sensing strategy, a sequential optimum design approach for the computation of vehicle-specific sensing trajectories with maximized information value is presented. In the last step, both approaches are combined to form a decentralized dynamic data-driven cooperative feedback control scheme. During development and implementation of all parts, particular attention is paid to efficiency and adaptability in order for the proposed scheme to be applied decentralized in possibly changing heterogeneous vehicle team constellations. Though atmospheric dispersion monitoring by UAVs serves as the motivating use case throughout this thesis, the developed solution is not limited to this specific scenario. In fact, it can easily be modified to deal with other kinds of unmanned vehicles or dynamic processes, and can, therefore, be applied to many other related problem types. Applicability, versatility, and effectiveness of the approach are successfully evaluated based on physics simulations of representative multi-objective monitoring scenarios.
Typ des Eintrags: | Dissertation | ||||
---|---|---|---|---|---|
Erschienen: | 2017 | ||||
Autor(en): | Euler, Juliane | ||||
Art des Eintrags: | Erstveröffentlichung | ||||
Titel: | Optimal Cooperative Control of UAVs for Dynamic Data-Driven Monitoring Tasks | ||||
Sprache: | Englisch | ||||
Referenten: | Stryk, Prof. Dr. Oskar von ; Rocha, Prof. Dr. Rui | ||||
Publikationsjahr: | Januar 2017 | ||||
Ort: | Darmstadt | ||||
Datum der mündlichen Prüfung: | 31 Januar 2017 | ||||
URL / URN: | http://tuprints.ulb.tu-darmstadt.de/7163 | ||||
Kurzbeschreibung (Abstract): | In recent years, there has been an immense improvement of methods and technology for Unmanned Aerial Vehicles (UAVs). By now, a steadily growing number of affordable platforms, as well as accurate onboard sensors, are available, which enables the use of UAVs as a remote sensing tool in various monitoring, surveillance, and disaster response tasks. This thesis deals with the challenging application scenario of monitoring atmospheric dispersion processes using multiple sensor-equipped UAVs. The idea is to enable the UAVs to autonomously move through the domain such that the utility of measurements taken along the way is maximized and cooperation among the team members is exploited. A three-part solution to this problem is developed. For cooperative control of multiple vehicles, a decentralized model-predictive control approach is proposed that is based on a mixed-integer linear system description. As data-driven adaptive sensing strategy, a sequential optimum design approach for the computation of vehicle-specific sensing trajectories with maximized information value is presented. In the last step, both approaches are combined to form a decentralized dynamic data-driven cooperative feedback control scheme. During development and implementation of all parts, particular attention is paid to efficiency and adaptability in order for the proposed scheme to be applied decentralized in possibly changing heterogeneous vehicle team constellations. Though atmospheric dispersion monitoring by UAVs serves as the motivating use case throughout this thesis, the developed solution is not limited to this specific scenario. In fact, it can easily be modified to deal with other kinds of unmanned vehicles or dynamic processes, and can, therefore, be applied to many other related problem types. Applicability, versatility, and effectiveness of the approach are successfully evaluated based on physics simulations of representative multi-objective monitoring scenarios. |
||||
Alternatives oder übersetztes Abstract: |
|
||||
URN: | urn:nbn:de:tuda-tuprints-71632 | ||||
Sachgruppe der Dewey Dezimalklassifikatin (DDC): | 000 Allgemeines, Informatik, Informationswissenschaft > 004 Informatik 500 Naturwissenschaften und Mathematik > 510 Mathematik 600 Technik, Medizin, angewandte Wissenschaften > 620 Ingenieurwissenschaften und Maschinenbau |
||||
Fachbereich(e)/-gebiet(e): | 20 Fachbereich Informatik 20 Fachbereich Informatik > Simulation, Systemoptimierung und Robotik |
||||
Hinterlegungsdatum: | 04 Feb 2018 20:55 | ||||
Letzte Änderung: | 07 Dez 2018 15:22 | ||||
PPN: | |||||
Referenten: | Stryk, Prof. Dr. Oskar von ; Rocha, Prof. Dr. Rui | ||||
Datum der mündlichen Prüfung / Verteidigung / mdl. Prüfung: | 31 Januar 2017 | ||||
Export: | |||||
Suche nach Titel in: | TUfind oder in Google |
Frage zum Eintrag |
Optionen (nur für Redakteure)
Redaktionelle Details anzeigen |