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SYSTEMS AND METHODS FOR ADVANCE ANOMALY DETECTION IN A DISCRETE MANUFACTURING PROCESS WITH A TASK PERFORMED BY A HUMAN-ROBOT TEAM
SYSTEMS AND METHODS FOR ADVANCE ANOMALY DETECTION IN A DISCRETE MANUFACTURING PROCESS WITH A TASK PERFORMED BY A HUMAN-ROBOT TEAM
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机译:在离散制造过程中提前异常检测的系统和方法,由人机团队执行的任务
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摘要
A system for detection of an anomaly in a discrete manufacturing process (DMP) with human-robot teams executing a task. Receive signals including robot, worker and DMP signals. Predict a sequence of events (SOEs) from DMP signals. Determine whether the predicted SOEs in the DMP signals is inconsistent with a behavior of operation of the DMP described in a DMP model, and if the predicted SOEs from DMP signals is inconsistent with the behavior, then an alarm is to be signaled. Input worker data into a Human Performance (HP) model, to obtain a state of the worker based on previously learned boundaries of human state. The state of the HW is then input into the HRI model and the DMP model to determine a classification of anomaly or no anomaly. Update a Human-Robot Interaction (HRI) model to obtain a control action of a robot or a type of an anomaly alarm.
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