HMAPs_IROS2018.pdf (5.28 MB)
HMAPs - Hybrid height-Voxel maps for environment representation
conference contribution
posted on 2019-03-19, 09:17 authored by Luis Garrote, Cristiano Premebida, David Silva, Urbano NunesThis paper presents a hybrid 3D-like grid-based
mapping approach, that we called HMAP, used as a reliable
and efficient 3D representation of the environment surrounding
a mobile robot. Considering 3D point-clouds as input data, the
proposed mapping approach addresses the representation of
height-voxel (HVoxel) elements inside the HMAP, where free
and occupied space is modeled through HVoxels, resulting in
a reliable method for 3D representation. The proposed method
corrects some of the problems inherent to the representation of
complex environments based on 2D and 2.5D representations,
while keeping an updated grid representation. Additionally,
we also propose a complete pipeline for SLAM based on
HMAPs. Indoor and outdoor experiments were carried out
to validate the proposed representation using data from a
Microsoft Kinect One (indoor) and a Velodyne VLP-16 LiDAR
(outdoor). The obtained results show that HMAPs can provide
a more detailed view of complex elements in a scene when
compared to a classic 2.5D representation. Moreover, validation
of the proposed SLAM approach was carried out in an outdoor
dataset with promising results, which lay a foundation for
further research in the topic.
Funding
Part of this work has been supported by UID/EEA/00048/2013, AGVPOSYS (CENTRO-01-0247-FEDER-003503) and MATIS (CENTRO-01-0145-FEDER-000014) projects, with FEDER funding, programs PT2020 and CENTRO2020
History
School
- Aeronautical, Automotive, Chemical and Materials Engineering
Department
- Aeronautical and Automotive Engineering
Published in
2018 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (IROS)Pages
1197 - 1203Citation
GARROTE, L. ... et al., 2018. HMAPs - Hybrid height-Voxel maps for environment representation. 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Madrid, Spain, October 1-5, pp. 1197 - 1203.Publisher
© IEEEVersion
- AM (Accepted Manuscript)
Publication date
2018Notes
© 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other worksISBN
9781538680940ISSN
2153-0858Publisher version
Language
- en