Evaluation of Crowd Models Under Various Environments for Robot Navigation Simulator

Abstract

Robot simulators are commonly employed in the study of autonomous mobile robots operating in human-robot coexistence environments. In these simulators, it is essential to place moving pedestrians as dynamic obstacles, which requires the application of various crowd models developed in the field of crowd simulation. However, existing crowd models often assume that all agents, including both pedestrians and robots, follow the same navigation algorithms. The validity of using such models for robot simulators remains unclear. This paper aims to explore the impact of robots with different navigation methods than pedestrians and the environment in which they are placed on the behavior and performance of crowd models in a robot navigation simulator. The experimental environment is constructed within a mobile robot simulator in which multiple agents, including robots, are deployed and crowd simulations are performed. These simulations are performed by moving the agents through multiple crowd models. In addition, the impact of the presence of robots and environmental factors on the performance of the crowd models is evaluated. The results indicate that the performance of the crowd models is highly dependent on the environment in which the robot operates, and that it is necessary to select the appropriate model for a given environment.