Research On Interactive Model Of Human-Robot Collaborative Performance

Robot technology is gradually becoming popular.It frees people from the heavy pressure of life and production,and provides more high-quality information services.However,traditional human-robot interaction used to be limited to a binary relationship.In recent years,how to use robots to enhance human capabilities has become a research hotspot.The rise of ubiquitous computing has laid the foundation for efficient information exchange between humans and robots,and has also opened up a broad space for exploring new human-robot interactive modes.The explicit and implicit collaborative interactive model proposed in this paper is based on the framework of ubiquitous computing.It is used for skill-centered interactive tasks and meets user utility-oriented interactive requirements.The model integrates the advantages of explicit interaction and implicit interaction,and fully considers the two key factors of user and context.The paper takes glove puppetry as an example to construct a human-robot collaborative performance system,focusing on the value of this new type of human-robot interactive model in the field of performing arts.The system aims to help users reduce cognitive burden,enhance performance effects and improve participation experience in performance interactive tasks.To this end,it digitizes performance information from explicit and implicit interaction channels,and adds a natural user interface based on gesture interaction,so as to realize the robot’s decision-making and execution,as well as the balance and adaptation mechanism between humans and robots.In the evaluation of this system,three experiments were set up to test the performance of the collaborative performance system in glove puppetry,and to prove the effectiveness of the explicit and implicit collaborative interactive model for performance interactive tasks from the decision-making and execution levels.The results also show that the new type of model has great development potential and application prospects.It will be suitable for a wider range of human-robot interaction research and assist interactive design work in other cross-domains.