In order to solve the problems that it is difficult for service robots to accurately understand pedestrian intentions and unreasonable obstacle avoidance path selection in dynamic pedestrian environment, a pedestrian openness comfort model was proposed. Firstly, by extending the traditional two-dimensional symmetric Gaussian function to an asymmetric Gaussian function, the dynamic comfort space of pedestrians can be modeled more accurately. Secondly, combined with the pedestrian′s head posture and pedestrian′s openness characteristics, the robot′s ability to understand the pedestrian′s movement intention and social interaction relationship is enhanced, so as to improve the friendliness and rationality of navigation. Finally, through the comparison and verification of simulation and experiments in the real environment, the service robot using the pedestrian openness comfort model is more optimized in path selection, and can actively avoid the interactive space of pedestrian groups, which not only reduces the possibility of conflict with pedestrians, but also enhances the smoothness and naturalness of navigation, and shortens the movement time by 1.15 and 2.58 s respectively in the simulation environment of different scenes. In the real environment of different scenes, the exercise time was shortened by 1.14, 2.30 and 0.12 s, respectively. Experimental results show that the model can effectively adapt the robot to complex pedestrian dynamic scenes, improve the efficiency of obstacle avoidance, and significantly improve the social friendliness and navigation quality of the robot in the human-machine integration scene.