Environment recognition for navigation of autonomous wheelchair from a video image

The Japanese population has rapidly aged and the number of aged persons who have lower physical ability has increased recently. Thus the development of medical and healthcare devices is expected. Wheelchair requires care support in most cases. Therefore the development of autonomous wheelchair is meaningful since we can expect to improve convenience and to reduce burden of caregivers. The autonomous wheelchair requires several techniques. Our research is to develop a navigation system based on image processing techniques. However, we assume that the system instructs an appropriate direction to head towards the destination when a wheelchair user comes to a crossing. Incidentally, deep learning, a kind of artificial neural network, has attracted attention in the field of machine learning in recent years. This paper proposes methodology for supporting autonomous driving by use of a classifier trained on a video images with deep learning. Also, we apply visual odometry to generate training data.