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Situational Awareness and Problems of Its Formation in the Tasks of UAV Behavior Control
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Situational awareness formation is one of the most critical elements in solving the problem of UAV behavior control. It aims to provide information support for UAV behavior control according to its objectives and tasks to be completed. We consider the UAV to be a type of controlled dynamic system. The article shows the place of UAVs in the hierarchy of dynamic systems. We introduce the concepts of UAV behavior and activity and formulate requirements for algorithms for controlling UAV behavior. We propose the concept of situational awareness as applied to the problem of behavior control of highly autonomous UAVs (HA-UAVs) and analyze the levels and types of this situational awareness. We show the specifics of situational awareness formation for UAVs and analyze its differences from situational awareness for manned aviation and remotely piloted UAVs. We propose the concept of situational awareness as applied to the problem of UAV behavior control and analyze the levels and types of this situational awareness. We highlight and discuss in more detail two crucial elements of situational awareness for HA-UAVs. The first of them is related to the analysis and prediction of the behavior of objects in the vicinity of the HA-UAV. The general considerations involved in solving this problem, including the problem of analyzing the group behavior of such objects, are discussed. As an illustrative example, the solution to the problem of tracking an aircraft maneuvering in the vicinity of a HA-UAV is given. The second element of situational awareness is related to the processing of visual information, which is one of the primary sources of situational awareness formation required for the operation of the HA-UAV control system. As an example here, we consider solving the problem of semantic segmentation of images processed when selecting a landing site for the HA-UAV in unfamiliar terrain. Both of these problems are solved using machine learning methods and tools. In the field of situational awareness for HA-UAVs, there are several problems that need to be solved. We formulate some of these problems and briefly describe them.
Title: Situational Awareness and Problems of Its Formation in the Tasks of UAV Behavior Control
Description:
Situational awareness formation is one of the most critical elements in solving the problem of UAV behavior control.
It aims to provide information support for UAV behavior control according to its objectives and tasks to be completed.
We consider the UAV to be a type of controlled dynamic system.
The article shows the place of UAVs in the hierarchy of dynamic systems.
We introduce the concepts of UAV behavior and activity and formulate requirements for algorithms for controlling UAV behavior.
We propose the concept of situational awareness as applied to the problem of behavior control of highly autonomous UAVs (HA-UAVs) and analyze the levels and types of this situational awareness.
We show the specifics of situational awareness formation for UAVs and analyze its differences from situational awareness for manned aviation and remotely piloted UAVs.
We propose the concept of situational awareness as applied to the problem of UAV behavior control and analyze the levels and types of this situational awareness.
We highlight and discuss in more detail two crucial elements of situational awareness for HA-UAVs.
The first of them is related to the analysis and prediction of the behavior of objects in the vicinity of the HA-UAV.
The general considerations involved in solving this problem, including the problem of analyzing the group behavior of such objects, are discussed.
As an illustrative example, the solution to the problem of tracking an aircraft maneuvering in the vicinity of a HA-UAV is given.
The second element of situational awareness is related to the processing of visual information, which is one of the primary sources of situational awareness formation required for the operation of the HA-UAV control system.
As an example here, we consider solving the problem of semantic segmentation of images processed when selecting a landing site for the HA-UAV in unfamiliar terrain.
Both of these problems are solved using machine learning methods and tools.
In the field of situational awareness for HA-UAVs, there are several problems that need to be solved.
We formulate some of these problems and briefly describe them.
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