at Google ScholarTitle data
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
. - pp. 75-80
DOI: https://doi.org/10.1109/RAAD.2010.5524605
Abstract in another language
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.
Further data
| Item Type: | Article in a book |
|---|---|
| Refereed: | Yes |
| 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 |
| Institutions of the University: | Faculties > Faculty of Mathematics, Physics und Computer Science > Department of Computer Science > Chair Applied Computer Science III > Chair Applied Computer Science III - Univ.-Prof. Dr. Dominik Henrich |
| Result of work at the UBT: | Yes |
| DDC Subjects: | 000 Computer Science, information, general works > 004 Computer science |
| Date Deposited: | 20 Feb 2025 14:08 |
| Last Modified: | 20 Feb 2025 14:08 |
| URI: | https://eref.uni-bayreuth.de/id/eprint/92501 |