Unmanned aerial vehicle operator state evaluation method based on multi-sensor measurement and neural network learning

Abstract

The invention provides an unmanned aerial vehicle operator state evaluation method based on multi-sensor measurement and neural network learning. A mapping relation between a sensor characteristic and a semanteme is established, thereby estimating a decision grade of an operator. The method has advantages of facilitating more visual mastering of real-time operator state, estimating whether the operator is suitable for a task, and performing corresponding adjustment on the task. Because a neural network learning method is utilized, a characteristic space of different operators can be established. Therefore, the unmanned aerial vehicle operator state evaluation method is suitable for various grades of unmanned aerial vehicle operators with different proficiencies.

Description

technical field [0001] The invention relates to the technical field of unmanned aerial vehicle systems, in particular to a method for assessing the state of an unmanned aerial vehicle operator based on multi-sensor measurement and neural network learning. Background technique [0002] With the improvement of the automation of UAVs, the operator's control of UAVs has changed from low-level behavior-based control to high-level knowledge-based control. This knowledge-based control is supervisory control. In supervisory control, flight control is done automatically by the system, and the operator is mainly responsible for high-level mission management and load management. Traditional command and control of a drone often requires multiple operators, while supervisory control makes it possible for a single operator to control multiple drones. On the one hand, the improvement of platform automation provides technical support for this transformation. On the other hand, Network-cent...

AI Technical Summary

Problems solved by technology

The ground station operator still has the final decision to control the aircraft during the execution of the mission. The UAV system is still a human-in-the-loop system. Its combat use cannot be separated from the command and control of humans. Increased workload and operational difficulty for station operators can easily lead to misjudgments and misoperations

Images