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Performance Analysis of ORB-SLAM in Foggy Environments

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Robot 2023: Sixth Iberian Robotics Conference (ROBOT 2023)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 976))

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Abstract

Vision based localization approaches, be Simultaneous Localization and Mapping (SLAM) or Visual Odometry (VO), rely heavily on distinct features detectable and trackable across different frames. Therefore, state of the art approaches utilize features that are scale-invariant, visible from different points of view, and are also tolerant to changes in light. However, visibility of the feature points are affected also by haze, mist or fog, which are atmospheric phenomena that vary across the day, effectively hindering the performance of vision based SLAM/VO approaches. In this work, we study the effect of fog on SLAM, particularly ORB-SLAM. We analyze the changes in the quality and quantity of the features with varying fog levels, as well as the quality of the eventual path generated by SLAM. We also show that performance of SLAM in foggy conditions can be improved by defogging the images, though only to a limited extent depending on the amount of fog in the environment.

This work was supported by AM2R project “Mobilizing Agenda for business innovation in the Two Wheels sector” funded by PRR - Recovery and Resilience Plan and by the Next Generation EU Fund, under reference C644866475-00000012 | 7253; and ILAF project “Intelligent Logistic Autonomous Fleet”, under Grant POCI-01-0247-FEDER-072534.

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Authors and Affiliations

  1. Institute of Systems and Robotics, Department of Electrical and Computer Engineering, University of Coimbra, 3030-290, Coimbra, Portugal

    Rita Singéis, Sedat Dogru & Lino Marques

Authors
  1. Rita Singéis
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  2. Sedat Dogru
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  3. Lino Marques
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Corresponding author

Correspondence to Sedat Dogru .

Editor information

Editors and Affiliations

  1. Dep. de Eng. Electrotecnica e de Computadores, University of Coimbra, Coimbra, Portugal

    Lino Marques

  2. Department of Electrónica Industrial, University of Minho, Escola de Engenharia, Guimarães, Portugal

    Cristina Santos

  3. Department of Electrical Engineering, Polytechnic Institute of Bragança, Bragança, Portugal

    José Luís Lima

  4. Centro Universitario de la Defensa, Zaragoza, Spain

    Danilo Tardioli

  5. Centre for Automation and Robotics UPM-CSIC, Universidad Politecnica de Madrid, Madrid, Spain

    Manuel Ferre

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Singéis, R., Dogru, S., Marques, L. (2024). Performance Analysis of ORB-SLAM in Foggy Environments. In: Marques, L., Santos, C., Lima, J.L., Tardioli, D., Ferre, M. (eds) Robot 2023: Sixth Iberian Robotics Conference. ROBOT 2023. Lecture Notes in Networks and Systems, vol 976. Springer, Cham. https://doi.org/10.1007/978-3-031-58676-7_17

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