Hohmann, Nikolas ; Bujny, Mariusz ; Adamy, Jürgen ; Olhofer, Markus (2022)
Multi-objective 3D Path Planning for UAVs in Large-Scale Urban Scenarios.
2022 IEEE Congress on Evolutionary Computation (CEC). Padua, Italy (18.-23.07.2022)
doi: 10.26083/tuprints-00022339
Konferenzveröffentlichung, Zweitveröffentlichung, Postprint
Kurzbeschreibung (Abstract)
In the context of real-world path planning applications for Unmanned Aerial Vehicles (UAVs), aspects such as handling of multiple objectives (e.g., minimizing risk, path length, travel time, energy consumption, or noise pollution), generation of smooth trajectories in 3D space, and the ability to deal with urban environments have to be taken into account jointly by an optimization algorithm to provide practically feasible solutions. Since the currently available methods do not allow for that, in this paper, we propose a holistic approach for solving a Multi-Objective Path Planning (MOPP) problem for UAVs in a three-dimensional, large-scale urban environment. For the tackled optimization problem, we propose an energy model and a noise model for a UAV, following a smooth 3D path. We utilize a path representation based on 3D Non-Uniform Rational B-Splines (NURBS). As optimizers, we use a conventional version of an Evolution Strategy (ES), two standard Multi-Objective Evolutionary Algorithms (MOEAs) – NSGA2 and MO-CMA-ES, and a gradient-based L-BFGS-B approach. To guide the optimization, we propose hybrid versions of the mentioned algorithms by applying an advanced initialization scheme that is based on the exact bidirectional Dijkstra algorithm. We compare the different algorithms with and without hybrid initialization in a statistical analysis, which considers the number of function evaluations and quality features of the obtained Pareto fronts indicating convergence and diversity of the solutions. We evaluate the methods on a realistic 3D urban path planning scenario in New York City, based on real-world data exported from OpenStreetMap. The examination’s results indicate that hybrid initialization is the main factor for the efficient identification of near-optimal solutions.
| Typ des Eintrags: | Konferenzveröffentlichung |
|---|---|
| Erschienen: | 2022 |
| Autor(en): | Hohmann, Nikolas ; Bujny, Mariusz ; Adamy, Jürgen ; Olhofer, Markus |
| Art des Eintrags: | Zweitveröffentlichung |
| Titel: | Multi-objective 3D Path Planning for UAVs in Large-Scale Urban Scenarios |
| Sprache: | Englisch |
| Publikationsjahr: | 2022 |
| Ort: | Darmstadt |
| Verlag: | IEEE |
| Buchtitel: | 2022 IEEE Congress on Evolutionary Computation (CEC) : 2022 Conference Proceedings |
| Kollation: | 8 Seiten |
| Veranstaltungstitel: | 2022 IEEE Congress on Evolutionary Computation (CEC) |
| Veranstaltungsort: | Padua, Italy |
| Veranstaltungsdatum: | 18.-23.07.2022 |
| DOI: | 10.26083/tuprints-00022339 |
| URL / URN: | https://tuprints.ulb.tu-darmstadt.de/22339 |
| Zugehörige Links: | |
| Herkunft: | Zweitveröffentlichungsservice |
| Kurzbeschreibung (Abstract): | In the context of real-world path planning applications for Unmanned Aerial Vehicles (UAVs), aspects such as handling of multiple objectives (e.g., minimizing risk, path length, travel time, energy consumption, or noise pollution), generation of smooth trajectories in 3D space, and the ability to deal with urban environments have to be taken into account jointly by an optimization algorithm to provide practically feasible solutions. Since the currently available methods do not allow for that, in this paper, we propose a holistic approach for solving a Multi-Objective Path Planning (MOPP) problem for UAVs in a three-dimensional, large-scale urban environment. For the tackled optimization problem, we propose an energy model and a noise model for a UAV, following a smooth 3D path. We utilize a path representation based on 3D Non-Uniform Rational B-Splines (NURBS). As optimizers, we use a conventional version of an Evolution Strategy (ES), two standard Multi-Objective Evolutionary Algorithms (MOEAs) – NSGA2 and MO-CMA-ES, and a gradient-based L-BFGS-B approach. To guide the optimization, we propose hybrid versions of the mentioned algorithms by applying an advanced initialization scheme that is based on the exact bidirectional Dijkstra algorithm. We compare the different algorithms with and without hybrid initialization in a statistical analysis, which considers the number of function evaluations and quality features of the obtained Pareto fronts indicating convergence and diversity of the solutions. We evaluate the methods on a realistic 3D urban path planning scenario in New York City, based on real-world data exported from OpenStreetMap. The examination’s results indicate that hybrid initialization is the main factor for the efficient identification of near-optimal solutions. |
| Freie Schlagworte: | Solid modeling, Surface reconstruction, Three-dimensional displays, Urban areas, Evolutionary computation, Autonomous aerial vehicles, Trajectory, multi-objective optimization, three-dimensional, path planning, hybrid algorithms, evolutionary algorithms, UAV, unmanned aerial vehicle |
| Status: | Postprint |
| URN: | urn:nbn:de:tuda-tuprints-223392 |
| 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): | 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 > Regelungsmethoden und Robotik (ab 01.08.2022 umbenannt in Regelungsmethoden und Intelligente Systeme) |
| Hinterlegungsdatum: | 16 Sep 2022 12:16 |
| Letzte Änderung: | 19 Sep 2022 13:33 |
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