Arenz, Oleg ; Abdulsamad, Hany ; Neumann, Gerhard (2022)
Optimal Control and Inverse Optimal Control by Distribution Matching.
2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). Daejeon, Korea (09.10.2016-14.10.2016)
doi: 10.26083/tuprints-00022929
Konferenzveröffentlichung, Zweitveröffentlichung, Postprint
 | Es ist eine neuere Version dieses Eintrags verfügbar. |
Kurzbeschreibung (Abstract)
Optimal control is a powerful approach to achieve optimal behavior. However, it typically requires a manual specification of a cost function which often contains several objectives, such as reaching goal positions at different time steps or energy efficiency. Manually trading-off these objectives is often difficult and requires a high engineering effort. In this paper, we present a new approach to specify optimal behavior. We directly specify the desired behavior by a distribution over future states or features of the states. For example, the experimenter could choose to reach certain mean positions with given accuracy/variance at specified time steps. Our approach also unifies optimal control and inverse optimal control in one framework. Given a desired state distribution, we estimate a cost function such that the optimal controller matches the desired distribution. If the desired distribution is estimated from expert demonstrations, our approach performs inverse optimal control. We evaluate our approach on several optimal and inverse optimal control tasks on non-linear systems using incremental linearizations similar to differential dynamic programming approaches.
| Typ des Eintrags: | Konferenzveröffentlichung |
|---|---|
| Erschienen: | 2022 |
| Autor(en): | Arenz, Oleg ; Abdulsamad, Hany ; Neumann, Gerhard |
| Art des Eintrags: | Zweitveröffentlichung |
| Titel: | Optimal Control and Inverse Optimal Control by Distribution Matching |
| Sprache: | Englisch |
| Publikationsjahr: | 2022 |
| Ort: | Darmstadt |
| Publikationsdatum der Erstveröffentlichung: | 2016 |
| Verlag: | IEEE |
| Buchtitel: | 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) |
| Kollation: | 14 ungezählte Seiten |
| Veranstaltungstitel: | 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) |
| Veranstaltungsort: | Daejeon, Korea |
| Veranstaltungsdatum: | 09.10.2016-14.10.2016 |
| DOI: | 10.26083/tuprints-00022929 |
| URL / URN: | https://tuprints.ulb.tu-darmstadt.de/22929 |
| Zugehörige Links: | |
| Herkunft: | Zweitveröffentlichungsservice |
| Kurzbeschreibung (Abstract): | Optimal control is a powerful approach to achieve optimal behavior. However, it typically requires a manual specification of a cost function which often contains several objectives, such as reaching goal positions at different time steps or energy efficiency. Manually trading-off these objectives is often difficult and requires a high engineering effort. In this paper, we present a new approach to specify optimal behavior. We directly specify the desired behavior by a distribution over future states or features of the states. For example, the experimenter could choose to reach certain mean positions with given accuracy/variance at specified time steps. Our approach also unifies optimal control and inverse optimal control in one framework. Given a desired state distribution, we estimate a cost function such that the optimal controller matches the desired distribution. If the desired distribution is estimated from expert demonstrations, our approach performs inverse optimal control. We evaluate our approach on several optimal and inverse optimal control tasks on non-linear systems using incremental linearizations similar to differential dynamic programming approaches. |
| Freie Schlagworte: | Optimal control, Entropy, Heuristic algorithms, Trajectory, Cost function, Learning (artificial intelligence) |
| Status: | Postprint |
| URN: | urn:nbn:de:tuda-tuprints-229290 |
| Sachgruppe der Dewey Dezimalklassifikatin (DDC): | 000 Allgemeines, Informatik, Informationswissenschaft > 004 Informatik |
| Fachbereich(e)/-gebiet(e): | 20 Fachbereich Informatik 20 Fachbereich Informatik > Intelligente Autonome Systeme |
| Hinterlegungsdatum: | 25 Nov 2022 12:51 |
| Letzte Änderung: | 08 Aug 2023 12:13 |
| PPN: | 503350850 |
| Export: | |
| Suche nach Titel in: | TUfind oder in Google |
Verfügbare Versionen dieses Eintrags
- Optimal Control and Inverse Optimal Control by Distribution Matching. (deposited 25 Nov 2022 12:51) [Gegenwärtig angezeigt]
 |
Frage zum Eintrag |
Optionen (nur für Redakteure)
 |
Redaktionelle Details anzeigen |
Drucken
Impressum