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Proceedings Paper

Novel approach of better understanding the complicated environment from the laser radar's range data
Author(s): Zhenmin Tang; Jingyu Yang; Chunli Fan; Bing Wang; Zhen Ding
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Paper Abstract

One of the most important aspects in the navigation of ALV is computer vision or machine vision. Usually, it is achieved by using multisensor fusion technology. As we know, laser radar is a typical sensor in this project, especially in the situation that there is an obstacle in a road. It is often effective to describe the relationship between road and obstacle by using height matrix from range data. However, when the front view is more complicated, such as a wall or a building on which exists a hole or a corridor big enough for ALV to go through, the above method may not be well done. For this reason, we propose a novel approach by using two matrixes from the range data to solve the problem. The main idea is that from the range data we figure out two matrixes, one is the height matrix, representing the height of the object from the horizontal plane, the other is the depth matrix representing the depth of the object from the laser radar vertical plane. By using the information of both height and depth, we can understand the front environment more precise and better.

Paper Details

Date Published: 23 September 1994
PDF: 8 pages
Proc. SPIE 2271, Industrial Applications of Laser Radar, (23 September 1994); doi: 10.1117/12.188162
Show Author Affiliations
Zhenmin Tang, East China Institute of Technology (China)
Jingyu Yang, East China Institute of Technology (China)
Chunli Fan, East China Institute of Technology (China)
Bing Wang, East China Institute of Technology (China)
Zhen Ding, East China Institute of Technology (China)

Published in SPIE Proceedings Vol. 2271:
Industrial Applications of Laser Radar
Gary W. Kamerman; William E. Keicher, Editor(s)

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