This paper presents an improved path planning method based on the artificial potential field method, firstly, based on the linkage between the subjective evaluation of emotionality (Self-Assessment Manikin,SAM) and emotional physiological responses (Emotional Physiological Responses, EPR) an evaluation system around the emotions is proposed to achieve the emotional visualization representation. Secondly, a human–computer interaction experimental platform combined with Virtual Reality (VR) technology is established to characterize physiological signals with the distance between the obstacle and the target point as the primary influencing factor, and to study the changing law of human emotions, so as to establish an emotional model of the distance between the obstacle and the target point. Finally, combining the evaluation system and the emotional model, the artificial emotional potential field path planning algorithm (Artificial emotional potential field, AEPF) is proposed, which improves the satisfaction during human–robot interaction on the basis of optimizing the robot’s driving path. The conclusion shows that, compared with the artificial potential field method, 80% of the subjects think that the robot has lower arousal and relatively smoother emotional feelings during traveling according to the artificial emotional potential field method, and at the same time, it provides a new idea for the sense of experience in the process of human–robot interaction.