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Multi-Drone Cooperation for Improved LiDAR-Based Mapping.

Flavia Causa1, Roberto Opromolla1, Giancarmine Fasano1

  • 1Department of Industrial Engineering, University of Naples "Federico II", 80125 Naples, Italy.

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Summary

This study introduces cooperative navigation for multi-drone LiDAR mapping, enhancing data collection and accuracy. Cooperative navigation significantly reduces georeferencing errors for Unmanned Aerial Vehicles (UAVs).

Keywords:
LiDAR mappingattitude requirementscooperative UAVscooperative mappingcooperative navigationgeoreferencing accuracypoint-density prediction

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Area of Science:

  • Robotics
  • Geomatics Engineering
  • Computer Vision

Background:

  • Accurate georeferencing of LiDAR data is crucial for effective mapping.
  • Multi-drone systems offer enhanced data collection capabilities but require sophisticated navigation strategies.
  • Cooperative navigation addresses challenges in Unmanned Aerial Vehicle (UAV) coordination for complex missions.

Purpose of the Study:

  • To develop and validate mission planning and cooperative navigation algorithms for multi-drone LiDAR mapping.
  • To demonstrate improved LiDAR data georeferencing accuracy and collection efficiency through UAV cooperation.
  • To provide analytical tools for optimizing mission parameters and formation geometry.

Main Methods:

  • Exploitation of the Coupled Differential GPS/Vision (CDGNSS/Vision) paradigm.
  • Definition of optimal formation geometry and Unmanned Aerial Vehicle (UAV) trajectories.
  • Development of analytical tools for point density estimation and attitude/pointing requirement definition.
  • Centralized cooperation-aware mission planning for complete coverage.

Main Results:

  • Cooperative navigation significantly reduces angular and positioning estimation uncertainties.
  • Achieved an order of magnitude reduction in georeferencing error, down to 16.7 cm in simulations.
  • Demonstrated improved data collection capabilities, including increased coverage per unit time and point cloud density.
  • Validated the proposed framework through numerical simulations for a powerline inspection mission.

Conclusions:

  • Cooperative navigation is essential for achieving high-accuracy LiDAR mapping with multi-drone systems.
  • The proposed framework effectively supports mission planning for complete coverage and enhanced data quality.
  • The integration of CDGNSS/Vision and optimized trajectories leads to substantial improvements in georeferencing precision.