Eiband, Thomas und Saveriano, Matteo und Lee, Dongheui (2019) Intuitive Programming of Conditional Tasks by Demonstration of Multiple Solutions. IEEE Robotics and Automation Letters, 4 (4), Seiten 4483-4490. IEEE - Institute of Electrical and Electronics Engineers. doi: 10.1109/LRA.2019.2935381. ISSN 2377-3766.
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Offizielle URL: https://ieeexplore.ieee.org/abstract/document/8798604
Kurzfassung
Conditional tasks include a decision on how the robot should react to an observation. This requires to select the appropriate action during execution. For instance, spatial sorting of objects may require different goal positions based on the objects properties, such as weight or geometry. We propose a framework that allows a user to demonstrate conditional tasks including recovery behaviors for expected situations. In our framework, human demonstrations define the required actions for task completion, which we term solutions. Each specific solution accounts for different conditions which may arise during execution. We exploit a clustering scheme to assign multiple demonstrations to a specific solution, which is then encoded in a probabilistic model. At runtime, our approach monitors the execution of the current solution using measured robot pose, external wrench, and grasp status. Deviations from the expected state are then classified as anomalies. This triggers the execution of an alternative solution, appropriately selected from the pool of demonstrated actions. Experiments on a real robot show the capability of the proposed approach to detect anomalies online and switch to an appropriate solution that fulfills the task.
elib-URL des Eintrags: | https://elib.dlr.de/128977/ | ||||||||||||||||
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Dokumentart: | Zeitschriftenbeitrag | ||||||||||||||||
Titel: | Intuitive Programming of Conditional Tasks by Demonstration of Multiple Solutions | ||||||||||||||||
Autoren: |
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Datum: | 14 August 2019 | ||||||||||||||||
Erschienen in: | IEEE Robotics and Automation Letters | ||||||||||||||||
Referierte Publikation: | Ja | ||||||||||||||||
Open Access: | Ja | ||||||||||||||||
Gold Open Access: | Nein | ||||||||||||||||
In SCOPUS: | Ja | ||||||||||||||||
In ISI Web of Science: | Ja | ||||||||||||||||
Band: | 4 | ||||||||||||||||
DOI: | 10.1109/LRA.2019.2935381 | ||||||||||||||||
Seitenbereich: | Seiten 4483-4490 | ||||||||||||||||
Herausgeber: |
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Verlag: | IEEE - Institute of Electrical and Electronics Engineers | ||||||||||||||||
ISSN: | 2377-3766 | ||||||||||||||||
Status: | veröffentlicht | ||||||||||||||||
Stichwörter: | Task analysis, Robot sensing systems, Monitoring, Force, Time series analysis, Switches, Learning from demonstration, failure detection and recovery, learning and adaptive systems | ||||||||||||||||
HGF - Forschungsbereich: | Luftfahrt, Raumfahrt und Verkehr | ||||||||||||||||
HGF - Programm: | Raumfahrt | ||||||||||||||||
HGF - Programmthema: | Technik für Raumfahrtsysteme | ||||||||||||||||
DLR - Schwerpunkt: | Raumfahrt | ||||||||||||||||
DLR - Forschungsgebiet: | R SY - Technik für Raumfahrtsysteme | ||||||||||||||||
DLR - Teilgebiet (Projekt, Vorhaben): | R - Intuitive Mensch-Roboter Schnittstelle [SY], Vorhaben Autonome, lernende Roboter (alt) | ||||||||||||||||
Standort: | Oberpfaffenhofen | ||||||||||||||||
Institute & Einrichtungen: | Institut für Robotik und Mechatronik (ab 2013) | ||||||||||||||||
Hinterlegt von: | Eiband, Thomas | ||||||||||||||||
Hinterlegt am: | 18 Nov 2019 08:52 | ||||||||||||||||
Letzte Änderung: | 08 Nov 2023 08:17 |
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