HMAPs_IROS2018.pdf (5.28 MB)
Download file

HMAPs - Hybrid height-Voxel maps for environment representation

Download (5.28 MB)
conference contribution
posted on 19.03.2019, 09:17 by Luis Garrote, Cristiano Premebida, David Silva, Urbano Nunes
This 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 - 1203

Citation

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

© IEEE

Version

AM (Accepted Manuscript)

Publication date

2018

Notes

© 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 works

ISBN

9781538680940

ISSN

2153-0858

Language

en

Usage metrics

Keywords

Exports