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相关概念视频

Field Application of Global Positioning System01:28

Field Application of Global Positioning System

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The Global Positioning System (GPS) has become an indispensable tool in fieldwork, offering unparalleled precision and efficiency for surveying, navigation, and infrastructure development. By harnessing signals from a constellation of satellites, GPS receivers determine the location of objects with remarkable speed and accuracy, often completing calculations within a second.Advantages of Modern GPS TechnologyContemporary GPS receivers are designed to meet the practical demands of field...
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Absolute Motion Analysis- General Plane Motion01:24

Absolute Motion Analysis- General Plane Motion

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Visualize a drone, with its propellers spinning rapidly, hovering mid-air. The fascinating movements and operations of this drone can be comprehended by applying the principle of general plane motion.
As the drone's propellers rotate, an upward force is generated that counteracts the force of gravity, enabling the drone to lift off from the ground. This initial movement of the drone is along a straight path, representing a form of translational motion. In this phase, every point on the...
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PI Controller: Design01:24

PI Controller: Design

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Proportional Integral (PI) controllers are a fundamental component in modern control systems, widely used to enhance performance and mitigate steady-state errors. They are particularly effective in applications such as automatic brightness adjustment on smartphones, where they excel at mitigating steady-state errors for step-function inputs. Unlike PD controllers, which require time-varying errors to function optimally, PI controllers leverage their integral component to address residual...
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Control Systems: Applications01:25

Control Systems: Applications

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Electrical engineering plays a pivotal role in our daily lives, with control systems at the heart of many applications, from home appliances to sophisticated space shuttles. Control systems manage and regulate the behavior of devices and processes, ensuring they function safely, correctly, and efficiently.
In modern vehicles, control systems manage various functions to enhance performance and safety. The steering wheel and accelerator are primary inputs in a car's control system. The...
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Introduction to Global Positioning System01:30

Introduction to Global Positioning System

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The Global Positioning System (GPS) revolutionized positioning on Earth, providing precise location data through satellite ranging. The GPS system was developed in 1978 by the U.S. Department of Defense  for military use, and it became available for civilian applications in 1983, transforming fields including navigation, fleet management, and time synchronization for telecommunications systems.GPS consists of satellites in medium Earth orbit, about 20,200 kilometers above the surface,...
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Types of Global Positioning System Surveys01:30

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GPS surveying methods vary in application, accuracy, and data collection techniques, catering to diverse surveying and mapping needs. Static GPS, kinematic GPS, and real-time kinematic (RTK) surveying are widely used. Each technique offers distinct advantages.Static GPS involves placing one receiver at a known reference point and another at the target point. It collects exact positional data by observing multiple satellite ranges over an extended period, achieving centimeter-level accuracy for...
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Automated Deployment of an Internet Protocol Telephony Service on Unmanned Aerial Vehicles Using Network Functions Virtualization
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对于无人机辅助物联网应用程序的延迟告知智能形成控制.

Lihan Liu1, Mengjiao Xu2, Zhuwei Wang2

  • 1School of Statistics and Data Science, Beijing Wuzi University, Beijing 101149, China.

Sensors (Basel, Switzerland)
|July 14, 2023
PubMed
概括
此摘要是机器生成的。

本研究引入了一种深度强化学习方法,用于控制组合中的多个无人机 (UAV). 拟议的算法有效地管理通信延迟,提高监控系统的性能.

关键词:
动态领先速度的速度.形成控制的形成控制.智能控制策略 智能控制策略监控监督监督监督监督监督监督监督监督监督监督监督监督监督监督监督监督监督时间延迟时间延迟

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科学领域:

  • 机器人和控制系统 机器人和控制系统
  • 人工智能的人工智能
  • 物联网 (IoT) 的物联网 (IoT) 的物联网.

背景情况:

  • 无人驾驶飞行器 (UAV) 对于物联网应用越来越重要,形成飞行增强了监视和安全.
  • 领导者-追随者方法通过专注于领导者的轨迹来简化无人机形成控制.
  • 动态领导速度和通信时间延迟对实时无人机形成控制构成重大挑战.

研究的目的:

  • 在具有通信延迟的高流动性场景中,研究使用深度强化学习 (DRL) 进行无人机形成跟踪的设计.
  • 将无人机形成问题表达为考虑通信延迟的状态错误最小化问题.
  • 开发一个DRL算法,能够弥补因时间延迟造成的性能下降.

主要方法:

  • 用二次性成本函数将无人机形成问题作为状态错误最小化的表述.
  • 开发一个以延迟为基础的马尔科夫决策流程 (DIMDP),结合先前的行动来减轻时间延迟的影响.
  • 关于基于延长延迟的深度决定性政策梯度 (DIDDPG) 算法的建议.

主要成果:

  • 拟议的DIDDPG算法有效地弥补了通信时间延迟造成的性能下降.
  • 数字实验验证了算法的能力,尽管延迟,保持稳定的形成跟踪.
  • 该研究分析了计算复杂性和不同时间延迟对系统性能的影响.

结论:

  • 深度增强学习提供了一个强大的解决方案,用于在有通信延迟的情况下控制无人机的形成.
  • 开发的DIDDPG算法为高流动性场景的实时UAV形成跟踪提供了显著的进步.
  • 该方法可以扩展到任意通信延迟场景,扩大其适用性.