Development of a guide-dog robot: human–robot interface considering walking conditions for a visually handicapped person

Abstract

The repletion rate of guide dogs for visually handicapped persons is roughly 10% nationwide. The reasons for this low rate are the long training period and the expense for obtaining a guide dog in Japan. Motivated by these two reasons, we are developing guide-dog robots. The major objective is to develop an intelligent human–robot interface. This paper describes two novel interface algorithms and strategy to guide visually handicapped person. We developed new leading edge searching method, which uses a single laser range finder (LRF) developed to find the center of the corridor in an indoor environment. We also developed a new twin cluster trace method that can recognize the led-person’s walking conditions measured by the LRF. The algorithm allows the guide-dog robot to accurately estimate and anticipate the led-person’s next move. We experimentally verified these algorithms. The results show that the algorithms are reliable enough to enable the guide-dog robot and the led-person to maneuver in a complex corridor environment.