Research on manned robot path expansion based on mixed social force model

Abstract

Aiming at the problem of how to safely and efficiently pass the manned robot in the dense crowd, the path extension algorithm based on the mixed social force model are studied. Firstly, starting from the traditional social force model, a mixed social force model is established in the scene of the integration of pedestrians and robots. Secondly, to address the problem of blocking the passage of robots in dense crowd, the interaction behavior is designed to trigger the movement of individual pedestrians, so that the distribution situation of the crowd that hinders the passage of robot is changed. Finally, guide the robot through the crowd according to the expansion of path until it reaches the destination. Simulation experiments show that the proposed algorithm can improve the passing efficiency of robot in indoor dynamic and static dense crowd environment.