Research on Recognition Method of Social Robot based on T-A-GCNIIT in Metaverse

Abstract

Social robots are used in intelligent customer service, intelligent chat, intelligent shopping guides, and more because of emotion recognition studies in cognitive psychology. However, determining the user's purpose fast and precisely has proved challenging. Domestic researchers proposed the A-GCNII model to address missing feature information, however it needs a lot of math. This research offers a social robot recognition approach using T-A-GCNIIT model and cognitive psychology to optimize computing complexity and performance. T-A-GCNIIT algorithm processes social network data, and Viola-Jones algorithm improves social robot intelligence to represent social robots in the meta-universe. The model performs well in node classification, link prediction, community discovery, and other tasks, with enhanced accuracy, recall, F1 score value, and other metrics. The model can also better comprehend the user's emotional state using cognitive psychology to better recognize their purpose and propose a fresh notion for enhancing social robots' cognitive psychology.