Title :
Improvement of assistive robot behavior by experience-based learning
Author_Institution :
Fachhochschule Frankfurt a.M. - Univ. of Appl. Sci., Frankfurt, Germany
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;
Conference_Titel :
Human System Interaction (HSI), 2013 The 6th International Conference on
Conference_Location :
Sopot
Print_ISBN :
978-1-4673-5635-0
DOI :
10.1109/HSI.2013.6577848
