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AAAI05-211.pdf
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🔗 Source: cdn.aaai.org
📊 Size: 721 KB
👤 Author: Rudolph Triebel
⬇️ Downloads: 24

Summary

The problem of learning volumetric maps from 3D range data in mobile robotics is challenging due to the large amount of data and the need to reduce it while maintaining accuracy. A novel approach is presented that estimates global constraints from the data and utilizes them to improve the registration process, resulting in highly accurate 3D models of the environment. The approach is based on the technique for consistent pose registration and extracts global constraints from 3D range scans, which are then used to improve the optimization process. Experiments carried out in simulation and with a mobile robot in an outdoor environment show that the approach yields more accurate models compared to a standard approach that does not utilize global constraints.

Description

The problem of learning volumetric maps from 3D range data in mobile robotics is challenging due to the large amount of data and the need to reduce it while...

Technical Information

  • File Format: PDF
  • File Size: 721 KB
  • Pages: 6
  • Language: EN
  • Author: Rudolph Triebel
  • Total Downloads: 24
  • Last Updated: 1 month ago

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