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To meet the demand for efficient autonomous navigation in logistics, this paper proposes a navigation system based on the Fast-LIO2 algorithm. This system achieves a robust real-time SLAM at a relatively low computational cost by tightly coupling 3D lidar and IMU with visual sensors. The stability experiment shows that in the warehouse environment, the positioning accuracy of this method has increased by more than 20%, and the positioning error is controlled within 0.05 m. This method operates stably on the microcomputer platform and is significantly superior to the traditional methods. The research also explored multimodal fusion strategies, providing a new direction for the development of lightweight logistics robots.

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Fast-LIO2 and Vision Fusion Logistics Walking System

  • 会议论文

  • 发表日期：

    2026年

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  • Xiangdong Xu,
  • Lichuan Ning,
  • Yuanmin Xie

摘要

To meet the demand for efficient autonomous navigation in logistics, this paper proposes a navigation system based on the Fast-LIO2 algorithm. This system achieves a robust real-time SLAM at a relatively low computational cost by tightly coupling 3D lidar and IMU with visual sensors. The stability experiment shows that in the warehouse environment, the positioning accuracy of this method has increased by more than 20%, and the positioning error is controlled within 0.05 m. This method operates stably on the microcomputer platform and is significantly superior to the traditional methods. The research also explored multimodal fusion strategies, providing a new direction for the development of lightweight logistics robots.