Modified Indoor Navigation Mapping based on VSLAM

DOI

10.2991/mecae-17.2017.40How to use a DOI?

Keywords

VSLAM, Navigation Mapping, Random Sample Consensus (RANSAC), Path Planning.

Abstract

Since the 2D maps built by traditional method are limited to describe single environment plane, the VSLAM-based indoor 2D map building method is proposed. The nonlinear optimization problem about camera poses is constructed based on VSLAM, and this problem is solved by Gauss-Newton method. Subsequently, the point cloud map of indoor environment is built. Then, based upon the RANSAC algorithm, the equation of ground plane is obtained. The point cloud of robots' passage area is projected onto the ground to form the grid map, and the indoor maps can be built by updating the grid occupied state based on Bayesian method. Experiments show that, compared with the 2D maps built by the traditional method, the maps built by our method contain the 3D structure information of environment. It helps robots avoid the suspended objects and the low objects successfully in the path planning experiment.

Copyright

© 2017, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Zhilin Lin
AU  - Guoliang Zhang
AU  - Erliang Yao
AU  - Xiao Jia
AU  - Hui Xu
PY  - 2017/03
DA  - 2017/03
TI  - Modified Indoor Navigation Mapping based on VSLAM
BT  - Proceedings of the 2017 International Conference on Mechanical, Electronic, Control and Automation Engineering (MECAE 2017)
PB  - Atlantis Press
SP  - 214
EP  - 220
SN  - 2352-5401
UR  - https://doi.org/10.2991/mecae-17.2017.40
DO  - 10.2991/mecae-17.2017.40
ID  - Lin2017/03
ER  -