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Indoor Path-Planning Algorithm for UAV-Based Contact Inspection.

Luis Miguel González de Santos1, Ernesto Frías Nores1, Joaquín Martínez Sánchez1

  • 1CINTECX, GeoTECH Group, Campus Universitario de Vigo, University of Vigo, As Lagoas, Marcosende, 36310 Vigo, Spain.

Sensors (Basel, Switzerland)
|January 22, 2021
PubMed
Summary
This summary is machine-generated.

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This study introduces a real-time path planning algorithm for unmanned aerial vehicles (UAVs) navigating indoor spaces. The algorithm efficiently plans inspection routes using building point clouds, achieving rapid path calculations.

Area of Science:

  • Robotics
  • Computer Vision
  • Artificial Intelligence

Background:

  • Unmanned aerial vehicles (UAVs) are increasingly utilized for tasks like infrastructure inspection and surveillance.
  • Real-time navigation and path planning are critical for autonomous UAV operations, especially in complex indoor environments.
  • Existing methods may face challenges with computational load and real-time performance in dynamic or unknown indoor settings.

Purpose of the Study:

  • To develop and present a novel real-time path planning algorithm for UAVs specifically designed for contact inspection tasks within indoor environments.
  • To leverage building point cloud data as the sole input for navigation and path computation.
  • To optimize the algorithm for speed and reliability, ensuring practical applicability in real-world scenarios.

Main Methods:

Keywords:
NDTUAVautonomous navigationcontact inspectionindustrial inspectionpayload

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  • The algorithm employs a two-part approach: a pre-processing step and a real-time path planning step.
  • Pre-processing involves segmenting the input point cloud into distinct rooms and discretizing each room's space.
  • The real-time component focuses on rapid path calculation, benefiting from the computationally intensive pre-processing phase.

Main Results:

  • The developed algorithm successfully processes building point clouds to enable UAV navigation.
  • Path calculations are executed in real-time, with demonstrated speeds of 8-9 milliseconds per path.
  • Extensive testing across various buildings confirmed the algorithm's reliability and efficiency for route calculation.

Conclusions:

  • The proposed real-time path planning algorithm is highly efficient and suitable for UAV-based contact inspection in indoor environments.
  • By offloading computational load to a pre-processing stage, the algorithm achieves rapid path planning crucial for real-time applications.
  • The method provides a reliable and fast solution for autonomous UAV navigation using only point cloud data.