Leveraging 3-D Data for Whole Object Shape and Reflection Aware 2-D Map Building Articles uri icon

publication date

  • July 2024

start page

  • 21941

end page

  • 21948

issue

  • 14

volume

  • 24

International Standard Serial Number (ISSN)

  • 1530-437X

Electronic International Standard Serial Number (EISSN)

  • 1558-1748

abstract

  • Two-dimensional laser scan sensors stand out
    as the preferred choice for robot mapping applications. How ever, these sensors have a significant drawback. Encounter ing objects with varying shapes at different heights, such as
    tables, poses challenges for these sensors due to their lim ited detection capability resulting from their dimensionality.
    This limitation increases the risk of potential collisions. Addi tionally, there are multiple polished materials that generate
    noise due to reflection. In order to have a robust occupancy
    grid map representation, these problems must be addressed.
    This article proposes the usage of a 3-D laser scan sensor to
    generate a 2-D occupancy grid map that incorporates the complete geometry of objects and effectively filters out noise
    from reflective materials like glass. The main novelty of the method is that it takes advantage of all the available 3-D data
    to avoid any information loss about objects" shapes. Additionally, a new approach for filtering reflection noise based on
    the analysis of indoor structural elements is proposed. Both approaches are merged for the creation of a robust indoor
    representation that allows to safely navigate the environment. Finally, a recursive Bayesian filter is applied for merging
    data, so noise due to dynamic elements that appeared during data collection is also filtered. Experimental evaluations in
    indoor environments with diverse objects and reflective surfaces, including dynamic elements like people, demonstrate
    the effectiveness of the proposed approach.

subjects

  • Electronics
  • Robotics and Industrial Informatics

keywords

  • 3-d laser scan; occupancy grid map; reflection; robust map building