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Occupancy-elevation grid: an alternative approach for robotic mapping and navigation

Published online by Cambridge University Press:  15 April 2015

Anderson Souza  and
Luiz M. G. Gonçalves
Anderson Souza*
Affiliation:
Department of Informatics, University of State of the Rio Grande do Norte, Natal, Rio Grande do Norte, Brazil
Luiz M. G. Gonçalves
Affiliation:
Department of Computing Engineer and Automation, Federal University of the Rio Grande do Norte, Natal, Rio Grande do Norte, Brazil E-mail: [email protected]
*
*Corresponding author. E-mail: [email protected]
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Summary

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This paper proposes an alternative environment mapping method for accurate robotic navigation based on 3D information. Typical techniques for 3D mapping using occupancy grid require intensive computational workloads in order to both build and store the map. This work introduces an Occupancy-Elevation Grid (OEG) mapping technique, which is a discrete mapping approach where each cell represents the occupancy probability, the height of the terrain and its variance. This representation allows a mobile robot to know with an accurate degree of certainty whether a place in the environment is occupied by an obstacle and the height of such obstacle. Thus, based on its hardware characteristics, it can make calculations to decide if it is possible to traverse that specific place. In general, the map representation introduced can be used in conjunction with any kind of distance sensor. In this work, we use laser range data and stereo system data with a probabilistic treatment. The resulting maps allow the execution of tasks as decision making for autonomous navigation, exploration, localization and path planning, considering the existence and the height of the obstacles. Experiments carried out with real data demonstrate that the proposed approach yields useful maps for autonomous navigation.

Keywords

Grid mapsNavigationOccupancy-elevation mapping
Type
Articles
Information
Robotica , Volume 34 , Issue 11 , November 2016 , pp. 2592 - 2609
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/3.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited.
Copyright
Copyright © Cambridge University Press 2015

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