Research on SLAM of mobile robot based on fusion of laser and vision

Guoqing Qi; Daoyi Ma; Yunben Du; Xiangxiang Cao; Hao Chen

doi:10.1117/12.2671329

29 March 2023 Research on SLAM of mobile robot based on fusion of laser and vision

Guoqing Qi, Daoyi Ma, Yunben Du, Xiangxiang Cao, Hao Chen

Author Affiliations +

Proceedings Volume 12594, Second International Conference on Electronic Information Engineering and Computer Communication (EIECC 2022); 125940V (2023) https://doi.org/10.1117/12.2671329
Event: Second International Conference on Electronic Information Engineering and Computer Communication (EIECC 2022), 2022, Xi'an, China

Abstract

In the complex environment simultaneous localization and mapping (SLAM) system, the use of a single laser or visual sensor is susceptible to external factors, which affects the accuracy of mobile robot mapping. A SLAM mapping method based on vision, LIDAR and encoder fusion is designed. Firstly, LIDAR and encoder data are fused by extended Kalman filter (EKF) method. Then, the data obtained by the depth camera is converted into the virtual two-dimensional laser radar data. Through the adaptive weighted fusion algorithm, the EKF fusion results are weighted fusion with the camera processing data, and the fused data is used to construct the map. The experimental results of the actual environment show that the method of multi-sensor data fusion is better than single sensor in the accuracy of mapping, and can establish a map closer to the actual environment.

Citation Download Citation

Guoqing Qi, Daoyi Ma, Yunben Du, Xiangxiang Cao, and Hao Chen "Research on SLAM of mobile robot based on fusion of laser and vision", Proc. SPIE 12594, Second International Conference on Electronic Information Engineering and Computer Communication (EIECC 2022), 125940V (29 March 2023); https://doi.org/10.1117/12.2671329

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