Mobile robot considering a pedestrian walking model based on the environmental characteristics

In recent years, service robots have advanced toward having to the ability to move autonomously in an environment in which they co-exist with humans. Thus, the robots must engage in pedestrian avoidance to arrive at their goal point. Usually, these robots regard pedestrians as moving obstacle, so, the robots should plan the avoiding-path over the range of pedestrians moving area dynamically. However, it is inefficiently if the robot plans unnecessary large avoiding-path. On the other hand, too short avoiding-path causes a collision with pedestrian. For these problems, in our previous research, we developed a probability model, which shows the characteristics of the pedestrians' flow; they don't change moving direction suddenly and the predicted area is like a fan-shape. Furthermore, we proposed a robot navigation method depends on this probability model. Thus, our idea realizes both an effective path and pedestrian avoidance. However, this method did not consider the environmental factor and the characteristics of the pedestrian's walking are always constant. Actually, pedestrian's walking characteristics are different depending on the environment, for example, pedestrian's walking direction is various in free space model like shopping mall, in contrast, they are determined along the route in corridor model like an office. Thus, in this paper, we propose a new probability model depends on the environmental characteristics. In our proposed method, the robot detects pedestrian's walking flow based on the environmental characteristics and the robot makes pedestrian avoidance path by them during the robot navigation. We confirmed the proposed method is efficient by comparing experiments with the previous method, where the spread potential constant. The proposed method's effectiveness was confirmed through experiment with the prototype robot.