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Related Experiment Video

Updated: Feb 13, 2026

Simulation of a Scaled Assembly Process with Collaboration of a Robotic Arm and Monitoring through a Vision System for Quality Control
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Simulation of a Scaled Assembly Process with Collaboration of a Robotic Arm and Monitoring through a Vision System for Quality Control

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A Collaborative Approach for Surface Inspection Using Aerial Robots and Computer Vision.

Martin Molina1, Pedro Frau2, Dario Maravall3

  • 1Department of Artificial Intelligence, Technical University of Madrid, Boadilla del Monte, Madrid 28660, Spain. martin.molina@upm.es.

Sensors (Basel, Switzerland)
|March 23, 2018
PubMed
Summary
This summary is machine-generated.

This study introduces a semi-automatic approach for aerial robot surface inspection, enhancing autonomy through human-robot collaboration. Drones request human assistance when uncertain, improving anomaly detection in challenging environments.

Keywords:
Automated visual inspectionaerial roboticshuman-robot collaborationsurface inspection

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Area of Science:

  • Robotics
  • Computer Vision
  • Artificial Intelligence

Background:

  • Aerial robots with onboard cameras are crucial for inspecting hard-to-reach surfaces.
  • Increasing the autonomy of these robots is desirable for efficient inspection.
  • Current automated visual recognition methods struggle in uncontrolled environments, limiting fully automatic inspection.

Purpose of the Study:

  • To present a semi-automatic visual inspection solution that enhances aerial robot autonomy.
  • To enable human-robot collaboration for improved surface anomaly detection.
  • To address the limitations of fully automated inspection in real-world scenarios.

Main Methods:

  • Developed a semi-automatic approach based on human-robot collaboration.
  • Implemented a system where drones delegate exploration and recognition tasks.
  • Integrated a mechanism for drones to request human assistance when encountering uncertainty.

Main Results:

  • Validated the proposed solution through an experimental robotic system.
  • Utilized the Aerostack software framework for system development.
  • Demonstrated an increased degree of autonomy in detecting surface anomalies.

Conclusions:

  • The human-robot collaboration model significantly boosts aerial robot autonomy for surface inspection.
  • The developed system effectively handles uncertainty by seeking operator assistance.
  • This approach offers a practical solution for improving automated visual inspection capabilities.