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Article

DPCR-SLAM: A Dual-Point-Cloud-Registration SLAM Based on Line Features for Mapping an Indoor Mobile Robot

School of Artificial intelligence, South China Normal University, Foshan 528225, China
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Author to whom correspondence should be addressed.
Sensors 2025, 25(17), 5561; https://doi.org/10.3390/s25175561
Submission received: 13 August 2025 / Revised: 1 September 2025 / Accepted: 4 September 2025 / Published: 5 September 2025
(This article belongs to the Section Sensors and Robotics)

Abstract

Simultaneous Localization and Mapping (SLAM) systems require accurate and globally consistent mapping to ensure the long-term stable operation of robots or vehicles. However, for the commercial applications of indoor sweeping robots, the system needs to maintain accuracy while keeping computational and storage requirements low to ensure cost controllability. This paper proposes a dual-point-cloud-registration SLAM based on line features for the mapping of a mobile robot, named DPCR-SLAM. The front-end employs an improved Point-to-Line Iterative Closest Point (PLICP) algorithm for point cloud registration. It first aligns the point cloud and updates the submap. Subsequently, the submap is aligned with the regional map, which is then updated accordingly. The back-end uses the association between regional maps to perform graph optimization and update the global map. The experimental results show that, in the application scenario of indoor sweeping robots, the proposed method reduces the map storage space by 76.3%, the point cloud processing time by 55.8%, the graph optimization time by 77.7%, and the average localization error by 10.9% compared to the Cartographer, which is commonly used in the industry.
Keywords: Simultaneous Localization and Mapping; laser radar; optimization; Iterative Closest Point; real-time systems Simultaneous Localization and Mapping; laser radar; optimization; Iterative Closest Point; real-time systems

Share and Cite

MDPI and ACS Style

Cao, Y.; Ni, J.; Huang, Y. DPCR-SLAM: A Dual-Point-Cloud-Registration SLAM Based on Line Features for Mapping an Indoor Mobile Robot. Sensors 2025, 25, 5561. https://doi.org/10.3390/s25175561

AMA Style

Cao Y, Ni J, Huang Y. DPCR-SLAM: A Dual-Point-Cloud-Registration SLAM Based on Line Features for Mapping an Indoor Mobile Robot. Sensors. 2025; 25(17):5561. https://doi.org/10.3390/s25175561

Chicago/Turabian Style

Cao, Yibo, Junheng Ni, and Yonghao Huang. 2025. "DPCR-SLAM: A Dual-Point-Cloud-Registration SLAM Based on Line Features for Mapping an Indoor Mobile Robot" Sensors 25, no. 17: 5561. https://doi.org/10.3390/s25175561

APA Style

Cao, Y., Ni, J., & Huang, Y. (2025). DPCR-SLAM: A Dual-Point-Cloud-Registration SLAM Based on Line Features for Mapping an Indoor Mobile Robot. Sensors, 25(17), 5561. https://doi.org/10.3390/s25175561

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