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A Proposed System for Multi-UAVs in Remote Sensing Operations.

Pablo Flores Peña1,2, Marco Andrés Luna2,3, Mohammad Sadeq Ale Isaac3,4

  • 1Department of System Engineering and Automation, University Carlos III of Madrid, 28911 Leganés, Spain.

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Summary
This summary is machine-generated.

This study introduces advanced control and navigation for multi-unmanned aerial vehicle (UAV) systems in remote sensing. The designed system ensures robust attitude control and efficient multi-region path planning for optimal data collection.

Keywords:
UAV-Swarmcontrol strategiescoverage path planningremote sensing

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Area of Science:

  • Robotics and Control Systems
  • Aerospace Engineering
  • Remote Sensing Technology

Background:

  • Multi-unmanned aerial vehicle (UAV) systems are increasingly utilized for complex remote sensing operations.
  • Effective control and navigation are critical for mission success, particularly in dynamic environments.
  • Existing trajectory planning methods often struggle with multi-region coverage and optimization.

Purpose of the Study:

  • To design integrated communication, control, and navigation systems for multi-UAV remote sensing.
  • To develop a novel controller for dynamic attitude regulation of UAVs.
  • To create an optimized approach for multi-region coverage trajectory planning, addressing the Traveling Salesperson Problem with Chinese Postman Problem (TSP-CPP).

Main Methods:

  • A new controller combining a compensator and a nominal controller was designed for UAV attitude regulation.
  • A novel algorithm was developed to solve the multi-region coverage trajectory planning task (TSP-CPP).
  • Simulations were conducted using Matlab SimScape to test and optimize the integrated system.

Main Results:

  • The designed controller demonstrated robust performance in dynamically regulating UAV attitude.
  • The proposed navigation approach achieved optimal performance for multi-region coverage trajectory planning.
  • Simulations confirmed the effectiveness of the integrated control and navigation strategies.

Conclusions:

  • The developed multi-UAV system offers a robust and efficient solution for remote sensing operations.
  • The novel control and navigation algorithms significantly enhance the capabilities of UAVs in complex tasks.
  • This research provides a foundation for advanced autonomous remote sensing missions.