Smooth collision avoidance in human-robot coexisting environment

In order for service robots to safely coexist with humans, collision avoidance with humans is the most important issue. On the other hand, working efficiencies are also important and cannot be ignored. In this paper, we propose a method to estimate a pedestrian's behavior. Based on the estimation, we realize smooth collision avoidances between a robot and a human. A robot detects pedestrians by using a laser range finder and tracks them by a Kalman filter. We apply the social force model to the observed trajectory for a determination whether the pedestrian intends to avoid a collision with the robot or not. The robot selects an appropriate behavior based on the estimation results. We conducted experiments that a robot and a person pass each other. Through the experiments, the usefulness of the proposed method was demonstrated.