Real-time fusion study of raster maps based on feature matching

Xin Tong; Chao Chen; Cheng Xu; Xueting Pang

doi:10.1117/12.2684960

19 October 2023 Real-time fusion study of raster maps based on feature matching

Xin Tong, Chao Chen, Cheng Xu, Xueting Pang

Proceedings Volume 12709, Fourth International Conference on Artificial Intelligence and Electromechanical Automation (AIEA 2023); 127090M (2023) https://doi.org/10.1117/12.2684960
Event: Fourth International Conference on Artificial Intelligence and Electromechanical Automation (AIEA 2023), 2023, Nanjing, China

Abstract

Aiming at the problem of low mapping efficiency of Simultaneous Localization And Mapping (SLAM) algorithm for single robot, a real-time fusion scheme for multi-robot raster maps based on improved map_meiging package is designed, and the PROSAC algorithm with improved RANSAC algorithm is used to eliminate mismatched feature points and improve the efficiency of map fusion. Firstly, the two single robots construct local maps based on the Gmapping algorithm, and then extract the feature points of the raster map after grayscale processing, match and complete the map fusion after purification, which does not need to predict the initial pose of the mobile robot in advance. Finally, test experiments are carried out in the Gazebo simulation environment to verify the effectiveness, real-time and robustness of the method.

Citation Download Citation

Xin Tong, Chao Chen, Cheng Xu, and Xueting Pang "Real-time fusion study of raster maps based on feature matching", Proc. SPIE 12709, Fourth International Conference on Artificial Intelligence and Electromechanical Automation (AIEA 2023), 127090M (19 October 2023); https://doi.org/10.1117/12.2684960

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