Refine
H-BRS Bibliography
- yes (1168) (remove)
Departments, institutes and facilities
- Fachbereich Angewandte Naturwissenschaften (356)
- Fachbereich Wirtschaftswissenschaften (321)
- Fachbereich Informatik (186)
- Fachbereich Sozialpolitik und Soziale Sicherung (160)
- Fachbereich Ingenieurwissenschaften und Kommunikation (135)
- Institut für funktionale Gen-Analytik (IFGA) (112)
- Institut für Technik, Ressourcenschonung und Energieeffizienz (TREE) (83)
- Institute of Visual Computing (IVC) (35)
- Internationales Zentrum für Nachhaltige Entwicklung (IZNE) (25)
- Institut für Verbraucherinformatik (IVI) (22)
- Institut für Sicherheitsforschung (ISF) (19)
- Institut für Cyber Security & Privacy (ICSP) (17)
- Institut für Detektionstechnologien (IDT) (8)
- Zentrum für Ethik und Verantwortung (ZEV) (5)
- Centrum für Entrepreneurship, Innovation und Mittelstand (CENTIM) (4)
- Institut für Medienentwicklung und -analyse (IMEA) (3)
- Sprachenzentrum (3)
- Präsidium (2)
- Verwaltung (2)
- Bibliothek (1)
- Institut für Soziale Innovationen (ISI) (1)
- Zentrum für Innovation und Entwicklung in der Lehre (ZIEL) (1)
Document Type
- Article (1168) (remove)
Year of publication
Has Fulltext
- no (1168) (remove)
Keywords
- GC/MS (7)
- Qualitätsmanagement (6)
- Africa (5)
- Deutschland (5)
- ISM: molecules (5)
- Performance (5)
- Qualitätssicherung (5)
- Virtual reality (5)
- CD21 (4)
- Controlling (4)
Spektroskopische Qualifizierung und Quantifizierung von Hyaluronsäure in Nahrungsergänzungsmitteln
(2023)
Trueness and precision of milled and 3D printed root-analogue implants: A comparative in vitro study
(2023)
In the design of robot skills, the focus generally lies on increasing the flexibility and reliability of the robot execution process; however, typical skill representations are not designed for analysing execution failures if they occur or for explicitly learning from failures. In this paper, we describe a learning-based hybrid representation for skill parameterisation called an execution model, which considers execution failures to be a natural part of the execution process. We then (i) demonstrate how execution contexts can be included in execution models, (ii) introduce a technique for generalising models between object categories by combining generalisation attempts performed by a robot with knowledge about object similarities represented in an ontology, and (iii) describe a procedure that uses an execution model for identifying a likely hypothesis of a parameterisation failure. The feasibility of the proposed methods is evaluated in multiple experiments performed with a physical robot in the context of handle grasping, object grasping, and object pulling. The experimental results suggest that execution models contribute towards avoiding execution failures, but also represent a first step towards more introspective robots that are able to analyse some of their execution failures in an explicit manner.
Forget it!
(2023)