A New Method for Occupancy Grid Maps Merging: Application to Multi-vehicle Cooperative Local Mapping and Moving Object Detection in Outdoor Environment

Abstract : Autonomous mapping, especially in the form of SLAM (Simultaneous Localization And Mapping), has long since been used for many indoor robotic applications and is also useful in outdoor intelligent vehicle applications such as object detection. Most existing research works on environment mapping and object detection in outdoor applications have been dedicated to single vehicle system. On the other hand, multi-vehicle cooperative perception based on inter-vehicle data sharing can bring considerable benefits in many scenarios that are challenging for a single vehicle system. In this paper, a new method for occupancy grid maps merging is proposed: an objective function based on occupancy likelihood is introduced to measure the consistency degree of maps alignment; genetic algorithm implemented in a dynamic scheme is adopted to optimize the objective function. A scheme of multi-vehicle cooperative local mapping and moving object detection using the proposed occupancy grid maps merging method is also introduced. Real-data tests are given
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Communication dans un congrès
ICARCV 2012 - 12th International Conference on Control, Automation, Robotics and Vision, Dec 2012, Guangzhou, China. 2012
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Contributeur : Fawzi Nashashibi <>
Soumis le : mardi 18 décembre 2012 - 23:22:51
Dernière modification le : vendredi 25 mai 2018 - 12:02:03
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Hao Li, Fawzi Nashashibi. A New Method for Occupancy Grid Maps Merging: Application to Multi-vehicle Cooperative Local Mapping and Moving Object Detection in Outdoor Environment. ICARCV 2012 - 12th International Conference on Control, Automation, Robotics and Vision, Dec 2012, Guangzhou, China. 2012. 〈hal-00766777〉

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