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Proceedings Paper

Semantic map for service robot navigation based on ROS
Author(s): Jianhua Zhang; Wei He; Aidi Zhao; Lin Zhang; Qi Feng; Youjie Zhou
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Paper Abstract

The environment perception and navigation ability of robots are the basis of robot interaction with environment. The scene understanding is the prerequisite of robot autonomous navigation and navigation is the ultimate goal of robot scene understanding, therefore, a mobile robot semantic map navigation system is designed. Firstly, a dense pointcloud map is constructed by using a deep convolutional neural network. Then, the mapping relationship between the depth camera data and the laser data is proposed, for purpose of realizing their interconversion. And a method of constructing two-dimensional raster map by simulating laser data by using the data of the depth camera is proposed. Finally, a method that semantic information is integrated into the two-dimensional grid map is proposed, realizing the semantic navigation of the service robot. The experimental results showed that compared with other robotic navigation systems, the proposed algorithm can better realize the interactions between service robots and people and the environment.

Paper Details

Date Published: 31 January 2020
PDF: 8 pages
Proc. SPIE 11427, Second Target Recognition and Artificial Intelligence Summit Forum, 1142710 (31 January 2020); doi: 10.1117/12.2550936
Show Author Affiliations
Jianhua Zhang, Hebei Univ. of Technology (China)
Wei He, Hebei Univ. of Technology (China)
Aidi Zhao, Hebei Univ. of Technology (China)
Lin Zhang, Hebei Univ. of Technology (China)
Qi Feng, Hebei Univ. of Technology (China)
Youjie Zhou, Hebei Univ. of Technology (China)

Published in SPIE Proceedings Vol. 11427:
Second Target Recognition and Artificial Intelligence Summit Forum
Tianran Wang; Tianyou Chai; Huitao Fan; Qifeng Yu, Editor(s)

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