Epidemic prevention robot knowledge learning and migration method and system

Abstract

The invention provides an epidemic prevention robot knowledge learning and migration method and system, and the method comprises the steps: 1, building a subtask offline knowledge base based on manualand priori knowledge according to an epidemic prevention scene of a robot application; 2, constructing a subtask network model based on multiple tasks according to the offline knowledge base, and carrying out task migration learning training; 3, constructing a knowledge reasoning engine based on the sub-task network model and task transfer learning training; 4, constructing a knowledge graph according to a knowledge reasoning engine; 5, performing task environment-based mode training according to the knowledge graph; and 6, performing knowledge migration according to the mode training resultbased on the task environment. The robot can be widely used in epidemic prevention and control, so that manpower is liberated, the risk that workers are infected in epidemic prevention and control isreduced, and the method and system can play an important role in epidemic prevention and control.

Description

Technical field[0001]The invention relates to the technical field of epidemic prevention robots, in particular to a method and system for learning and migrating knowledge of epidemic prevention robots.Background technique[0002]With the sudden outbreak of the novel coronavirus COVID-19, the work and lives of people all over the world have been severely affected. With the development of the epidemic, the pressure on medical resources and public health resources has become more and more serious, and the problem of insufficient manpower and the high risk of infection of staff have become more and more serious. There is an urgent need for a measure to replace manpower.[0003]Robots are often used to perform dangerous and repetitive tasks to free up manpower. It happens to meet the requirements for epidemic prevention. Therefore, more and more places are considering the use of epidemic prevention robots for epidemic prevention and control. For epidemic prevention robots, its ability to lea...

AI Technical Summary

Problems solved by technology

For the anti-epidemic robot, its ability to learn and update continuously through autonomous learning is very necessary, but the traditional convolutional neural network has insufficient training samples, high training overhead, and few sample labels under the condition of small samples. It is difficult to apply in the epidemic prevention robot knowledge learning and transfer method proposed in this paper can just solve this problem

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