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A Real-Time Knowledge Scheme for Sensory-Controlled Robot Assembly Tasks

Simon, Wolfgang ; Ersü, Enis ; Gose, H. ; Zoll, M. (2023)
A Real-Time Knowledge Scheme for Sensory-Controlled Robot Assembly Tasks.
In: IFAC Proceedings Volumes, 1988, 21 (16)
doi: 10.26083/tuprints-00023390
Article, Secondary publication, Publisher's Version

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Item Type: Article
Type of entry: Secondary publication
Title: A Real-Time Knowledge Scheme for Sensory-Controlled Robot Assembly Tasks
Language: English
Date: 2023
Place of Publication: Darmstadt
Year of primary publication: 1988
Publisher: IFAC - International Federation of Automatic Control
Journal or Publication Title: IFAC Proceedings Volumes
Volume of the journal: 21
Issue Number: 16
DOI: 10.26083/tuprints-00023390
Corresponding Links:
Origin: Secondary publication service

In the field of assembly automation with industrial robots the research on the application of artificial intelligence techniques is getting increasing importance. This paper describes the hierarchical structure of a knowledge—based sensory-controlled robot assembly system under development which is capable to plan and execute assembly tasks under real—time requirements. The hybrid knowledge representation scheme combining the rule—based and object—oriented approach to represent the assembly domain—specific knowledge is discussed. Furtheron, the knowledge processing concept based upon the representation scheme is explained. A first prototype of the system has been implemented in a real robotic test—bed. Several peg/hole part mating sequences validated the capability of the system to execute assembly tasks in an uncertain environment using sensory information.

Uncontrolled Keywords: Artificial intelligence, assembling, knowledge base, knowledge representation, knowledge processing, robots
Status: Publisher's Version
URN: urn:nbn:de:tuda-tuprints-233909
Additional Information:

Zugl. Konferenzveröffentlichung: 2nd IFAC Symposium on Robot Control (SYROCO '88), 05.-07.10.1988, Karlsruhe, Federal Republic of Germany

Classification DDC: 600 Technology, medicine, applied sciences > 620 Engineering and machine engineering
Divisions: 18 Department of Electrical Engineering and Information Technology > Institut für Automatisierungstechnik und Mechatronik > Control Methods and Intelligent Systems
Date Deposited: 28 Apr 2023 08:05
Last Modified: 10 Jul 2023 12:33
URI: https://tuprints.ulb.tu-darmstadt.de/id/eprint/23390
PPN: 509466575
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