# How Do Humans Recognize the Motion Arousal of Non-Humanoid Robots?
## 1 Introduction
We tend to believe that order exists in things themselves, even when we know little about their nature. When our senses present the arrangement of things, we can easily imagine them. In other words, the human visual system ignores details to reduce cognitive load, so the judgment of emotional expression in movement is based on the perception of overall patterns. This point is also proven in the field of animation. For example, animation software summarizes movement patterns through limited operation methods, giving the illusion of life to various creatures and objects, allowing them to display emotions that humans can recognize. PIXAR's small desk lamp character is a classic case, conveying emotional content through actions without a humanoid appearance. In the context of the meta-verse, where reality and virtual space merge, robots have become a new form of animation. With the assistance of AI, they jump out of the screen and participate in human life. Therefore, this study aims to explore how humans perceive the movement and corresponding emotions of NHRs based on Gestalt psychology and to make assumptions about the expression patterns of NHR. This is intended to deepen our understanding of robot emotional expression and provide theoretical guidance for robot design. Thus, this study makes an overall hypothesis: Human recognition of a robot's emotional actions also stems from the perception of the overall movement, which is unrelated to the mechanical appearance. Furthermore, it considers the question of how humans recognize the arousal expressed through the movement of NHRs: Is there a movement element that can transcend appearance differences and express the emotion arousal of NHRs based on humans' underlying cognition? The innovations of this study are as follows:  
1. Perspective Innovation: Analyzing the emotional expression of NHRs from the perspective of human cognition breaks the limitations of traditional methods that rely solely on data-driven approaches. It provides theoretical support and practical guidance for the emotional interaction of NHR in complex environments. 2. Method Innovation: The proposal of using universal emotional expression elements that are not dependent on specific robot forms or designs can be migrated and applied across different types of NHR. This greatly enhances the universality and practicality of the research results. These elements are also highly replicable and iterative, providing a new basis for the application of machine learning algorithms on NHR. This helps accelerate knowledge accumulation and technological progress, laying the foundation for promoting multimodal and interdisciplinary research. 3. Application Innovation: By integrating interdisciplinary methods, theories from psychology and kinesiology are applied to the new field of NHR emotional expression research. This optimizes the human-robot interaction process, ensuring that even users without research experience in robotics can correctly understand the emotional expression of robots. As a result, the naturalness and accuracy of the emotional expression of NHR are improved. In the literature review section, this paper first introduces the concept of emotional dimensions and the expression of movement. It then analyzes the elements related to the expression of arousal and extracts elements that may have universal value as the research subjects. Following this, based on the theory of physical kinematics constraints, the paper classifies NHRs and identifies key research points that have been overlooked in previous studies. In the theory and hypothesis section, relevant hypotheses are proposed based on the literature analysis and they are tested in experiments. Then, a comprehensive discussion is conducted. Finally, a summary is provided to conclude the paper.