Segmentation and analysis of console operation using self-organizing map with cluster growing method

Authors:
Satoshi Suzuki;Fumio Harashima
Affiliations:
School of Science and Technology for Future Life, Department of Robotics and Mechatronics, Tokyo Denki University, Tokyo, Japan;Tokyo Metropolitan University, Tokyo, Japan
Venue:
IROS'09 Proceedings of the 2009 IEEE/RSJ international conference on Intelligent robots and systems
Year:
2009

Citing 4
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Abstract

For manipulation of remote mobile robots, adequate scheduling of tasks and selecting of operational commands are required. This paper presents an analysis procedure to make the task switching profile visible by utilizing the Self-Organizing Map (SOM) and new cluster growing method. For practical verification, an experiment system with radio-controlled construction equipments was built, and the proposed analysis procedure was applied to the experimental task. As a result, it was confirmed by correlation analysis that distances among decomposed clusters corresponding to segments of operation strongly relate to performance index of the task.