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Seamless Navigation, 3D Reconstruction, Thermographic and Semantic Mapping for Building Inspection.

Adrian Schischmanow1, Dennis Dahlke1, Dirk Baumbach1

  • 1Institute of Optical Sensor Systems, German Aerospace Center (DLR), 12489 Berlin, Germany.

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Summary
This summary is machine-generated.

This study introduces a workflow for real-time 3D thermal mapping and navigation, integrating indoor/outdoor data for enhanced inspection tasks. The system fuses visual-inertial navigation with thermal imaging and global referencing for automated 3D modeling.

Keywords:
3D thermal mappingabsolute referencingbuilding information model (BIM)building inspectionmulti-sensor data fusionpixel co-registrationreal-time self-localization and mappingseamless navigationsemantic modeltrifocal geometrical camera calibrationvisual aided inertial navigationvisual odometry

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Area of Science:

  • Geomatics Engineering
  • Robotics
  • Computer Vision

Background:

  • Accurate 3D mapping and thermal analysis are crucial for infrastructure inspection and time-critical applications.
  • Integrating indoor and outdoor spatial data presents significant technical challenges.
  • Existing methods often lack real-time capabilities or seamless global referencing.

Purpose of the Study:

  • To develop an automated workflow for real-time 3D thermal mapping and navigation in combined indoor/outdoor environments.
  • To enhance inspection tasks and time-critical applications through integrated sensor data.
  • To achieve seamless global referencing for georeferenced 3D point clouds.

Main Methods:

  • Utilized a hand-held integrated positioning system (IPS) with visual-aided inertial navigation.
  • Augmented the IPS with a passive thermal infrared camera and global referencing via surveyed optical markers (AprilTags).
  • Fused stereo camera and thermal image data, calibrated a trifocal camera system, and integrated UAV data for a complete building hull point cloud.

Main Results:

  • Generated a georeferenced 3D point cloud enriched with thermal intensity values.
  • Achieved seamless fusion of terrestrial and aerial datasets for comprehensive building data.
  • Demonstrated automated semantic 3D model reconstruction from fused sensor data.

Conclusions:

  • The presented workflow enables automated, real-time 3D thermal mapping and navigation in complex environments.
  • This approach significantly advances automated building information modeling (BIM) and inspection capabilities.
  • The successful demonstration on a test site validates the workflow's practical applicability.