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Related Concept Videos

Distributed Loads: Problem Solving01:21

Distributed Loads: Problem Solving

Beams are structural elements commonly employed in engineering applications requiring different load-carrying capacities. The first step in analyzing a beam under a distributed load is to simplify the problem by dividing the load into smaller regions, which allows one to consider each region separately and calculate the magnitude of the equivalent resultant load acting on each portion of the beam. The magnitude of the equivalent resultant load for each region can be determined by calculating...
Distributed Loads01:19

Distributed Loads

Distributed loads are a common type of load that engineers and scientists encounter in various practical situations. Distributed loads often refer to a type of load spread over a surface or a structure and can be modeled as continuous force per unit area.
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Maximum Power Flow and Line Loadability01:23

Maximum Power Flow and Line Loadability

The maximum power flow for lossy transmission lines is derived using ABCD parameters in phasor form. These parameters create a matrix relationship between the sending-end and receiving-end voltages and currents, allowing the determination of the receiving-end current. This relationship facilitates calculating the complex power delivered to the receiving end, from which real and reactive power components are derived.
Distribution Reliability and Automation01:25

Distribution Reliability and Automation

Distribution reliability in electrical power systems is critical for ensuring an uninterrupted power supply to consumers at minimal cost. According to IEEE Standard Terms, reliability is the probability that a device will function without failure over a specified time period or amount of usage. For electric power distribution, this translates to maintaining continuous power supply and addressing customer concerns over power outages. Several indices, as defined by IEEE Standard 1366-2012, are...
Transformers in Distribution System01:27

Transformers in Distribution System

Transformers in distribution systems can be broadly categorized into distribution substation transformers and other distribution transformers. They are crucial for stepping down high transmission voltages to levels suitable for distribution and end-user applications.
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Relative Motion Analysis using Rotating Axes-Problem Solving01:29

Relative Motion Analysis using Rotating Axes-Problem Solving

Consider a crane whose telescopic boom rotates with an angular velocity of 0.04 rad/s and angular acceleration of 0.02 rad/s2. Along with the rotation, the boom also extends linearly with a uniform speed of 5 m/s. The extension of the boom is measured at point D, which is measured with respect to the fixed point C on the other end of the boom. For the given instant, the distance between points C and D is 60 meters.
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Related Experiment Video

Updated: May 28, 2026

Automated Deployment of an Internet Protocol Telephony Service on Unmanned Aerial Vehicles Using Network Functions Virtualization
07:49

Automated Deployment of an Internet Protocol Telephony Service on Unmanned Aerial Vehicles Using Network Functions Virtualization

Published on: November 26, 2019

Multi-Objective Task Scheduling for Vehicle-UAV Synchronous Cooperative Distribution Network Inspection.

Xiaoyi Liu1, Yuhan Yin1, Kunxiao Wu1

  • 1School of Electrical Engineering, Southeast University, Nanjing 210096, China.

Sensors (Basel, Switzerland)
|May 27, 2026
PubMed
Summary
This summary is machine-generated.

This study introduces a novel vehicle-UAV cooperative inspection scheduling method using MOTD3-NSGA-II. The approach ensures 100% task coverage and efficient energy management for distribution network inspections.

Keywords:
deep reinforcement learningdistribution linemulti-objective optimizationunmanned aerial vehiclevehicle–UAV cooperative inspection

Related Experiment Videos

Last Updated: May 28, 2026

Automated Deployment of an Internet Protocol Telephony Service on Unmanned Aerial Vehicles Using Network Functions Virtualization
07:49

Automated Deployment of an Internet Protocol Telephony Service on Unmanned Aerial Vehicles Using Network Functions Virtualization

Published on: November 26, 2019

Area of Science:

  • Engineering
  • Robotics
  • Artificial Intelligence

Background:

  • Distribution network inspections face challenges including vehicle parking limitations, limited Unmanned Aerial Vehicle (UAV) endurance, and inefficient multi-task coordination.
  • Existing methods struggle to optimize the complex interplay between ground vehicles and UAVs for comprehensive inspection tasks.

Purpose of the Study:

  • To develop an intelligent task scheduling method for synchronous vehicle-UAV cooperative inspection of distribution networks.
  • To address constraints such as vehicle repositioning, UAV launch/landing, and battery state-of-charge (SoC) limitations.
  • To optimize multiple objectives including task coverage, mission completion time, residual SoC, and load balance.

Main Methods:

  • A vehicle-UAV synchronous cooperative inspection model was established, incorporating staged vehicle movements and UAV operational constraints.
  • A multi-objective optimization model was formulated using task coverage, mission time, minimum residual SoC, and load balance as key objectives.
  • A bi-level closed-loop solution framework was developed, utilizing Non-dominated Sorting Genetic Algorithm II (NSGA-II) for parameter optimization and Multi-Objective Twin Delayed Deep Deterministic Policy Gradient (MOTD3) for UAV scheduling policy learning.

Main Results:

  • The proposed MOTD3-NSGA-II method achieved 100% task coverage across all tested scenarios.
  • Mission completion times varied between 9693 s and 11,109 s, demonstrating efficient scheduling.
  • Minimum residual state of charge was maintained within a safe range of 0.28-0.36, ensuring energy safety.

Conclusions:

  • The developed method effectively balances inspection completeness, execution efficiency, energy safety, and cooperative stability in vehicle-UAV systems.
  • This approach offers a valuable reference for intelligent task scheduling in complex distribution network inspection scenarios.
  • The study highlights the potential of advanced reinforcement learning and multi-objective optimization for enhancing cooperative robotic systems.