Adjustment Ability of a Neural Network with Variable Type Connection Weights for Autonomous Obstacle Avoidance in a Intelligent Wheelchair

Abstract

In our research group, an assist method for human's operation of electric-powered wheelchairs has been investigated. The purpose of researches is to make powered wheelchair intelligent and to develop a mobility aid for people, who find it difficult or impossi-ble to drive a conventional electric powered wheelchair. On some prototype of our group, a neural network produces an obstacle avoidance function. In previous researches, we found that by varying connection weights of the neural network according to the condition of ob-stacles in the neighborhood of the wheelchair, the obstacle avoidance function is improved. In this research, we discuss the adjustment ability of a neural network with variable type connection weights based on numerical studies.