Research On Knowledge Evolution Of Industrial Cloud Robotics Driven By Dynamic Model

The development of emerging technologies such as cloud computing and big data makes it possible to integrate cloud technology with robots.The combination of cloud robots and industrial robots provides a new mode for robots in manufacturing field to perform tasks and share resources.The knowledge engineering of industrial cloud robotics(ICR)can realize knowledge exchange,sharing and creation,improve production efficiency,speed up decision-making and improve decision-making quality.Therefore,how to express the knowledge in the manufacturing process in a unified form,realize the sharing and circulation among robots and complete the evolution of knowledge model has important theoretical value and practical significance.However,the current research on knowledge engineering of robots mainly focuses on the knowledge application of traditional industrial robots in the field of manufacturing,while the knowledge management model of industrial cloud robotics is not perfect,so the research on knowledge evolution of industrial cloud robotics is of great significance.Aiming at the above problems,this paper focuses on the knowledge evolution of industrial cloud robotics driven by dynamic models,and the main research work is as follows:(1)The dynamic production information model of industrial cloud robotics is constructed.Starting with the production information knowledge of industrial cloud robotics in manufacturing field,the knowledge elements of production information model of industrial cloud robotics are determined.The related concepts,attributes and relationships of industrial robot model,process model and object model are analyzed,and the knowledge framework of production information model of industrial cloud robotics is constructed.The robot capability reasoning based on dynamic description logic,the process reasoning based on SWRL semantic rules and the object reasoning based on case model are studied.The dynamic modeling of industrial cloud robotics production information is completed by OWL ontology description language through dynamic knowledge reasoning.(2)The mechanism and method of knowledge evolution for industrial cloud robotics are proposed.The knowledge evolution mechanism of industrial cloud robotics is analyzed,and a knowledge evolution model framework based on the mechanism of "knowledge acquisition-interactive sharing-iterative updating" is proposed.The operation mechanism of the knowledge evolution model is elaborated in detail.In view of the dynamic changes of production information in manufacturing process,the incremental learning method is used to realize the incremental updating of attributes,objects and cases,and knowledge is reduced incrementally based on rough set theory to avoid rebuilding all original models.An assembly case is used to verify the validity of knowledge evolution mechanism and methods.(3)Based on the dynamic model of industrial cloud robotics,a system of industrial cloud robotics knowledge base is designed and developed to provide a knowledge base of manufacturing information shared by cloud platform.The system mainly includes knowledge representation module,knowledge reasoning module and knowledge evolution module.Its functions include the construction and visualization of knowledge model,knowledge retrieval of production information and knowledge recommendation of decision-making scheme,so as to transfer explicit and tacit knowledge in manufacturing environment,realize inheritance and innovation of knowledge in the application process,further accelerate production speed and enhance production efficiency.