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. © 2011 Springer-Verlag.