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Appearance-Based Sequential Robot Localization Using a Patchwise Approximation of a Descriptor Manifold.

Alberto Jaenal1, Francisco-Angel Moreno1, Javier Gonzalez-Jimenez1

  • 1Machine Perception and Intelligent Robotics Group (MAPIR), Department of System Engineering and Automation Biomedical Research Institute of Malaga (IBIMA), University of Malaga, 29071 Málaga, Spain.

Sensors (Basel, Switzerland)
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PubMed
Summary
This summary is machine-generated.

This study introduces a novel appearance-based robot localization method using an "appearance map" of image descriptors. The technique achieves robust and accurate 2D localization, outperforming existing methods.

Keywords:
Gaussian processesappearance-based localizationcomputer visiondescriptor manifoldimage manifoldindoor positioningmanifold learningrobot vision systems

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Area of Science:

  • Robotics
  • Computer Vision
  • Machine Learning

Background:

  • Appearance-based robot localization relies on visual cues.
  • Existing methods struggle with appearance variations and require dense maps.

Purpose of the Study:

  • To develop a robust and accurate appearance-based robot localization system.
  • To create a lightweight and efficient environment map for localization.

Main Methods:

  • Proposed a novel 'appearance map' using Patches of Smooth Appearance Change (PSACs).
  • Employed a Gaussian Process Particle Filter (GPPF) for camera tracking and Place Recognition (PR) for relocalization.
  • Utilized Gaussian Processes (GPs) trained per PSAC for descriptor regression and likelihood estimation.

Main Results:

  • Achieved median localization errors below 0.3 m and 6°.
  • Demonstrated superior robustness and accuracy compared to state-of-the-art methods.
  • Successfully handled appearance variations using GP white noise modeling.

Conclusions:

  • The proposed method offers a significant advancement in appearance-based robot localization.
  • The PSAC-based appearance map provides an efficient and effective representation for localization.
  • The GPPF and GP-based approach ensures reliable performance under changing environmental conditions.