Improvement of assistive robot behavior by experience-based learning

Author

Nauth, Peter

Author_Institution

Fachhochschule Frankfurt a.M. - Univ. of Appl. Sci., Frankfurt, Germany

fYear

2013

fDate

6-8 June 2013

Firstpage

363

Lastpage

367

Abstract

Robots designed for assisting humans in their homes need to adapt to the changing requirements of daily life. This requires multimodal sensor systems as well as learning strategies for understanding new goals and for recognizing new objects. However, coping with changes is not limited to environmental sensing. In order to achieve full autonomy, the robots must adapt their behavior due to good and bad experiences made. Concepts and first results of modelling intelligent sensing and adaptive behavior in an artificial mind as well as of merging mind and machine are presented in this paper.

Keywords

educational robots; human-robot interaction; intelligent robots; learning (artificial intelligence); object recognition; robot vision; sensors; service robots; adaptive behavior; artificial mind; assistive robot behavior; environmental sensing; experience-based learning; intelligent sensing modelling; learning strategies; multimodal sensor systems; object recognition; Adaptive Behavior; Autonomous Robots; Experience-based Learning; Human-Interactive Robots; Intelligent Multimodal Sensor Systems; Machine Learning; Robot Intelligence; Self-Generating Will;

fLanguage

English

Publisher

ieee

Conference_Titel

Human System Interaction (HSI), 2013 The 6th International Conference on

Conference_Location

Sopot

ISSN

2158-2246

Print_ISBN

978-1-4673-5635-0

Type

conf

DOI

10.1109/HSI.2013.6577848

Filename

6577848