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JACIII Vol.11 No.8 pp. 922-930
doi: 10.20965/jaciii.2007.p0922
(2007)

Paper:

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Adjustability of Neural Networks with Variant Connection Weights for Obstacle Avoidance in an Intelligent Wheelchair

Toshihiko Yasuda*, Hajime Tanaka*, Kazushi Nakamura**,
and Katsuyuki Tanaka*

*Dept. of Mechanical System Engineering, The University of Shiga Prefecture, 2500 Hassaka-cho, Hikone, Shiga 522-8533, Japan

**Dai Nippon Printing Co., Ltd., 1-1-1 Ichigaya, Kagacho, Shinjuku-ku, Tokyo 162-8001, Japan

Received:
March 14, 2007
Accepted:
June 26, 2007
Published:
October 20, 2007
Creative Commons License
Keywords:
neural network, variant connection weight, obstacle avoidance, operation assist, intelligent wheelchair
Abstract
We have been studying electrically powered wheelchair operation to make electrically powered wheelchair intelligent and to develop a mobility aid for those who find it difficult or impossible to use conventional electrically powered wheelchairs. Some of the prototypes we have developed use neural networks providing obstacle avoidance. In previous research, we found that by varying neural network connection weight based on obstacles in the wheelchair’s vicinity and its run state, obstacle avoidance is improved. In this research, we discuss the adjustability of neural networks with variant connection weight based on numerical studies.
Cite this article as:
T. Yasuda, H. Tanaka, K. Nakamura, and K. Tanaka, “Adjustability of Neural Networks with Variant Connection Weights for Obstacle Avoidance in an Intelligent Wheelchair,” J. Adv. Comput. Intell. Intell. Inform., Vol.11 No.8, pp. 922-930, 2007.
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