Gait measurement for human behavior estimation against autonomous mobile robot

Abstract

To realize a safe collision avoidance of autonomous mobile robots, understanding human behavior against the robots is important. This paper has proposed a gait measurement method for human behavior estimation against autonomous mobile robot. The proposed method using a laser range sensor consists of five observed leg patterns recognition and global nearest neighbor (GNN)-based data association with a variable validation region based on the state of each leg. To verify the effectiveness of the proposed system, a verification test in a hospital that staff is recruited as participants were carried out. From the experimental results in the hospital, we confirm that the proposed method can reduce the chance of losing track of both legs and the variable validation region can reduce the chance of false tracking.