NDLI: Environment recognition system based on multiple classification analyses for mobile robots

Content Provider	IEEE Xplore Digital Library
Author	Kanda, A. Ishii, K. Sato, M.
Copyright Year	2009
Description	Author affiliation: Fukuoka IST Fukuoka, Japan (Sato, M.) \|\| Kyushu Institute of Technology, KIT, Fukuoka, Japan (Kanda, A.; Ishii, K.)
Abstract	Various mobile mechanisms have been developed combining linkage mechanisms and wheels, and the combination of passive linkage mechanisms and small wheels is one of research trends to enhance the mobility on irregular terrain. We have been working on a 6-wheeled mobile robot employing a passive linkage mechanism, which achieved climbing capability over a 0.20[m] height of bump and stairs, and developed velocity controllers using PID and neural network. In this paper, we propose an environment recognition system for the wheeled mobile robot, where multiple classification analyses such as Self-Organizing Map, k-means method and Principle Component Analyses are introduced and used for clustering robot's environments based on state variables such as joint angles and velocities of links, and attitude angles of the robot body. We evaluate the recognition performance through experiments.
Starting Page	2782
Ending Page	2787
File Size	1276427
Page Count	6
File Format	PDF
ISBN	9781424427932
ISSN	1062922X
DOI	10.1109/ICSMC.2009.5346586
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-10-11
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Mobile robots Couplings Wheels Neural networks Control systems Three-term control Sampling methods Robot sensing systems Cybernetics USA Councils environment recognition wheeled mobile robot neural network self-organizing map
Content Type	Text
Resource Type	Article

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