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Crafting rational and imaginative choreographies remains a pivotal challenge for dance creators. Leveraging Internet of Things (IoT) technology and Human-Computer Interaction (HCI) interfaces, this project introduces an innovative methodology for designing dance training environments and integrates this approach into dance education. It involves a comparative analysis of the congruence between the dance poses executed by the robot and the authentic poses of human performers, offering a fresh perspective on the synergy between technology and the art of dance. The aim is to demonstrate that intelligent dance robots based on IoT and HCI interfaces combined with psychological space construction positively impact dance creativity. The research results indicate: (1) The knee joint pitch angle is measured, with the initial angle set at 1.2\u00a0rad. The final results show significant differences in the three groups compared to the initial value. (2) The hip joint pitch angle is measured, with the initial angle set at 0.3\u00a0rad. Group A is closer to the initially set angle. (3) The ankle joint pitch angle is measured, with the initial angle set at \u22120.2\u00a0rad. Compared to groups B and C, Group A\u2019s ankle joint pitch angle remains almost unchanged and is very close to the initial value. This research aims to simplify the computational process of parameter identification, ensuring that joint angles during dancing are more closely aligned with the initial angles and that the trajectory of angles is smoother. 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