Leveraging 3-D Data for Whole Object Shape and Reflection Aware 2-D Map Building
Articles
Overview
published in
- IEEE SENSORS JOURNAL Journal
publication date
- July 2024
start page
- 21941
end page
- 21948
issue
- 14
volume
- 24
Digital Object Identifier (DOI)
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.
Classification
subjects
- Electronics
- Robotics and Industrial Informatics
keywords
- 3-d laser scan; occupancy grid map; reflection; robust map building