Pfefferkorn, Maik ; Holzmann, Philipp ; Matschek, Janine ; Findeisen, Rolf (2022)
Safe Corridor Learning For Model Predictive Path Following Control.
In: IFAC-PapersOnLine, 55 (30)
doi: 10.1016/j.ifacol.2022.11.032
Artikel, Bibliographie
Kurzbeschreibung (Abstract)
Safe collision-free operation of autonomous systems, such as mobile robots in crowded, uncertain, only partially known environments, is challenging. We propose learning a collision-free corridor from demonstration via heteroscedastic Gaussian processes. We incorporate available deterministic obstacle information in the learning procedure to derive safety guarantees for the corridor. The learned passage is utilized in a model predictive path planning controller that steers the system safely through the environment. The achievable results are underlined in simulations considering a mobile robot.
| Typ des Eintrags: | Artikel |
|---|---|
| Erschienen: | 2022 |
| Autor(en): | Pfefferkorn, Maik ; Holzmann, Philipp ; Matschek, Janine ; Findeisen, Rolf |
| Art des Eintrags: | Bibliographie |
| Titel: | Safe Corridor Learning For Model Predictive Path Following Control |
| Sprache: | Englisch |
| Publikationsjahr: | 17 September 2022 |
| Verlag: | Elsevier |
| Titel der Zeitschrift, Zeitung oder Schriftenreihe: | IFAC-PapersOnLine |
| Jahrgang/Volume einer Zeitschrift: | 55 |
| (Heft-)Nummer: | 30 |
| Veranstaltungsdatum: | 12.09.2022-16.09.2022 |
| DOI: | 10.1016/j.ifacol.2022.11.032 |
| URL / URN: | https://www.sciencedirect.com/science/article/pii/S240589632... |
| Kurzbeschreibung (Abstract): | Safe collision-free operation of autonomous systems, such as mobile robots in crowded, uncertain, only partially known environments, is challenging. We propose learning a collision-free corridor from demonstration via heteroscedastic Gaussian processes. We incorporate available deterministic obstacle information in the learning procedure to derive safety guarantees for the corridor. The learned passage is utilized in a model predictive path planning controller that steers the system safely through the environment. The achievable results are underlined in simulations considering a mobile robot. |
| Zusätzliche Informationen: | 25th International Symposium on Mathematical Theory of Networks and Systems MTNS 2022, Bayreuth, Germany 12.-16.09.2022 |
| 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 > Control and Cyber-Physical Systems (CCPS) |
| Hinterlegungsdatum: | 13 Mär 2024 10:38 |
| Letzte Änderung: | 13 Jun 2024 14:44 |
| PPN: | 519125142 |
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