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A Multi-Layered 3D NDT Scan-Matching Method for Robust Localization in Logistics Warehouse Environments.

Taeho Kim1, Haneul Jeon1, Donghun Lee1

  • 1Mechanical Engineering Department, Soongsil University, Seoul 06978, Republic of Korea.

Sensors (Basel, Switzerland)
|March 11, 2023
PubMed
Summary

This study introduces a multi-layered 3D Normal Distribution Transform (NDT) scan-matching method for reliable robot localization in dynamic warehouses. The approach improves robustness by adapting to environmental changes at different height layers.

Keywords:
3D NDT scan-matching3D point-cloud mapIsaac simindoor navigationlocalization

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Area of Science:

  • Robotics
  • Computer Vision
  • Artificial Intelligence

Background:

  • Warehouse logistics presents significant challenges for robot localization due to dynamic environments and cluttered layouts.
  • Existing scan-matching methods struggle with the high variability and occlusions common in such settings.

Purpose of the Study:

  • To develop a robust 3D scan-matching approach for enhanced mobile robot localization in dynamic warehouse environments.
  • To improve localization accuracy and reliability by adapting to varying environmental conditions.

Main Methods:

  • A multi-layered 3D Normal Distribution Transform (NDT) scan-matching technique was proposed.
  • Point-cloud maps and scan measurements were partitioned into layers based on height and environmental change.
  • Covariance estimates for each layer were computed to assess localization uncertainty.

Main Results:

  • The multi-layered approach demonstrated improved localization robustness in cluttered and dynamic warehouse simulations.
  • Uncertainty estimation allowed for adaptive layer selection, switching to layers with lower uncertainty for better localization.
  • Simulation-based validation using Nvidia's Omniverse Isaac sim confirmed the method's effectiveness.

Conclusions:

  • The proposed multi-layered 3D NDT scan-matching method significantly enhances localization robustness in challenging warehouse environments.
  • This approach provides a foundation for addressing occlusion issues in mobile robot navigation within warehouses.
  • The adaptive layer selection strategy offers a novel solution for dynamic environment localization.