Terrain Recognition for Smart Wheelchair

Research interest in robotic wheelchairs is driven in part by their potential for improving the independence and quality-of-life of persons with disabilities and the elderly. However the large majority of research to date has focused on indoor operations. In this paper, we aim to develop a smart wheelchair robot system that moves independently in outdoor terrain smoothly. To achive this, we propose a robotic wheelchair system that is able to classify the type of outdoor terrain according to their roughness for the comfort of the user and also control the wheelchair movements to avoid drop-off and watery areas on the road. An artificial neural network based classifier is constructed to classify the patterns and features extracted from the Laser Range Sensor (LRS) intensity and distance data. The overall classification accuracy is 97.24 % using extracted features from the intensity and distance data. These classification results can in turn be used to control the motor of the smart wheelchair.

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