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Sensors 2014, 14(6), 10454-10478; doi:10.3390/s140610454
Article

Occupancy Grid Mapping in Urban Environments from a Moving On-Board Stereo-Vision System

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Received: 16 February 2014; in revised form: 30 May 2014 / Accepted: 9 June 2014 / Published: 13 June 2014
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Abstract: Occupancy grid map is a popular tool for representing the surrounding environments of mobile robots/intelligent vehicles. Its applications can be dated back to the 1980s, when researchers utilized sonar or LiDAR to illustrate environments by occupancy grids. However, in the literature, research on vision-based occupancy grid mapping is scant. Furthermore, when moving in a real dynamic world, traditional occupancy grid mapping is required not only with the ability to detect occupied areas, but also with the capability to understand dynamic environments. The paper addresses this issue by presenting a stereo-vision-based framework to create a dynamic occupancy grid map, which is applied in an intelligent vehicle driving in an urban scenario. Besides representing the surroundings as occupancy grids, dynamic occupancy grid mapping could provide the motion information of the grids. The proposed framework consists of two components. The first is motion estimation for the moving vehicle itself and independent moving objects. The second is dynamic occupancy grid mapping, which is based on the estimated motion information and the dense disparity map. The main benefit of the proposed framework is the ability of mapping occupied areas and moving objects at the same time. This is very practical in real applications. The proposed method is evaluated using real data acquired by our intelligent vehicle platform “SeTCar” in urban environments.
Keywords: occupancy grid map; U-V disparity image; intelligent vehicles occupancy grid map; U-V disparity image; intelligent vehicles
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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MDPI and ACS Style

Li, Y.; Ruichek, Y. Occupancy Grid Mapping in Urban Environments from a Moving On-Board Stereo-Vision System. Sensors 2014, 14, 10454-10478.

AMA Style

Li Y, Ruichek Y. Occupancy Grid Mapping in Urban Environments from a Moving On-Board Stereo-Vision System. Sensors. 2014; 14(6):10454-10478.

Chicago/Turabian Style

Li, You; Ruichek, Yassine. 2014. "Occupancy Grid Mapping in Urban Environments from a Moving On-Board Stereo-Vision System." Sensors 14, no. 6: 10454-10478.


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