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Awais, Muhammad ; Henrich, Dominik:
Human-Robot Collaboration by Intention recognition using Probabilistic State Machines.
In:
19th International Workshop on Robotics in Alpe-Adria-Danube Region. -
Budapest, Hungary
,
2010
. - S. 75-80
DOI: https://doi.org/10.1109/RAAD.2010.5524605
Abstract
Combining the intelligent and situation dependent decision making capabilities of a human with the accuracy and power of a robot, performance of many tasks can be improved. The human-robot collaboration scenarios are increasing. Human-robot interaction is not only restricted to the humanoid robots interacting with the humans or to the mobile service robots providing different services but also industrial robots opens a wide range of human-robot collaboration set-ups. Intention recognition plays a key role in intuitive human-robot collaboration. In this paper we present a novel approach for recognizing the human intention using weighted probabilistic state machines. We categorize the recognition task into two categories namely explicit and implicit intention communication. We present a general intention recognition approach that can be applied to any human-robot cooperation situation. The algorithm is tested with an industrial robotic arm.
Weitere Angaben
| Publikationsform: | Aufsatz in einem Buch |
|---|---|
| Begutachteter Beitrag: | Ja |
| Keywords: | Collaboration; Intelligent robots; Human robot interaction; Service robots; Layout; Humanoid robots; Collaborative work; Robot vision systems; Glass; Hidden Markov models; Intuitive Human-Robot Collaboration; Intention Recognition;Probabilistic State Machines |
| Institutionen der Universität: | Fakultäten > Fakultät für Mathematik, Physik und Informatik > Institut für Informatik > Lehrstuhl Angewandte Informatik III > Lehrstuhl Angewandte Informatik III - Univ.-Prof. Dr. Dominik Henrich |
| Titel an der UBT entstanden: | Ja |
| Themengebiete aus DDC: | 000 Informatik,Informationswissenschaft, allgemeine Werke > 004 Informatik |
| Eingestellt am: | 20 Feb 2025 14:08 |
| Letzte Änderung: | 20 Feb 2025 14:08 |
| URI: | https://eref.uni-bayreuth.de/id/eprint/92501 |