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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.

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