In this paper, we present a model for semantic memory that allows machines to collect information and experiences to become more proficient with time. After a semantic analysis of the data, information is stored in a knowledge graph which is  used to comprehend instructions, expressed in natural language , and execute the required tasks in a deterministic manner. This imparts industrial robots cognitive behavior and an intuitive user interface, which is most appreciated in an era, when collaborative robots are to work alongside humans. The paper outlines the architecture of the system together with a practical implementation of the proposal.
In this paper, we present a model for semantic memory that allows machines to collect information and experiences to become more proficient with time. Post semantic analysis of the sensory and other related data, the processed information is stored in the knowledge graph which is then used to comprehend the work instructions expressed in natural language . This imparts industrial robots cognitive behavior to execute the required tasks in a deterministic manner. The paper outlines the architecture of the system along with an implementation of the proposal.
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