Autonomous Mover with Social Distance Respect

Abstract

Modern robots need to interact with human and move around human environment, in places such as museums, restaurants, or supermarkets. Therefore, robots should have social navigation capability. This article uses object detection to detect pedestrians, fuses object detection result with lidar information to obtain the state of the pedestrian, and then changes the navigation path according to the calculated pedestrian state. When there are people face-to-face and talking to each other, the autonomous mover bypasses instead of passing through them. When pedestrian in front of the autonomous mover is crossing the autonomous mover from left to right, the autonomous mover turns left to pass the other side instead of going straight and blocking the pedestrian. Therefore, the autonomous mover can navigate without disturbing pedestrians and respect social distance.Our approach uses a single RGB camera and a one-line lidar to detect pedestrian and accomplish the two specific goals in the real world. We fuse lidar information and object detection result to obtain the position and face orientation of the pedestrian. We add a customized social layer to the cost map of an existing navigation system, and thus, change the original shortest path algorithm. The face-to-face and crossing scenarios are verified in the hall of a university department building.