Autonomous Cognition and Correction System of Robot Service Based on Emotional Information and Case-Based Reasoning

Abstract

In the human-robot coexisting environment, robots can not only autonomous cognition tasks and provide intelligent services, but also focus on the warmness of services. In this paper, human emotion and the real-time scene information are utilized to realize the intelligence and emotional intelligence of the service. Emotional information and case reasoning are combined to build an autonomous cognition and correction system of robot service. Case database based on smart space scene data containing user emotional information was established. Using nearest neighbor strategy for case retrieval, autonomous cognition by reusing source case results is achieved. The user preference model is combined with emotional feedback information to correct the service content. Simulation results show that the method can significantly improve the service quality of the service robot and the harmony of human-robot interaction.