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Related Experiment Video

Updated: Sep 11, 2025

Author Spotlight: Insights into the Analysis of Human Interaction with 3D Virtual Objects

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Published on: October 18, 2024

Three-Dimensional Environment Mapping with a Rotary-Driven Lidar in Real Time.

Baixin Tong¹, Fangdi Jiang¹, Bo Lu²

¹School of Optoelectronic Engineering, Changchun University of Science and Technology, Changchun 130022, China.

Sensors (Basel, Switzerland)

|August 14, 2025

Summary

This study introduces a novel rotary LiDAR system and LV-SLAM framework for 3D environment reconstruction, significantly improving accuracy and reducing errors in complex environments.

Keywords:

loop closure detection multi-sensor fusion point cloud simultaneous localization and mapping

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Area of Science:

Robotics and Computer Vision
3D Environment Reconstruction
Simultaneous Localization and Mapping (SLAM)

Background:

Traditional LiDAR systems face field-of-view limitations, leading to blind spots and incomplete 3D reconstructions.
Existing SLAM methods struggle with accuracy and robustness in complex, GNSS-denied environments.

Purpose of the Study:

To develop a novel 3D environment reconstruction approach overcoming LiDAR field-of-view limitations.
To enhance the accuracy and robustness of 3D reconstruction using a multi-sensor fusion framework.
To provide a high-fidelity 3D reconstruction solution for challenging environments.

Main Methods:

Designed a rotary-driven LiDAR mechanism for uniform, full-field-of-view scanning.
Developed the LiDAR-Visual SLAM (LV-SLAM) framework with multi-threaded feature registration.
Implemented a two-phase loop closure detection mechanism for improved accuracy and robustness.

Main Results:

LV-SLAM reduced average absolute trajectory error (ATE) from 6.90 m to 2.48 m on the KITTI benchmark.
Achieved lower relative pose error (RPE), indicating enhanced global consistency and reduced drift.
Real-world tests showed more complete reconstructions with fewer occlusions and geometric accuracy within 5 cm RMSE.

Conclusions:

The proposed rotary LiDAR and LV-SLAM system offers a robust and accurate solution for high-fidelity 3D reconstruction.
The system effectively overcomes field-of-view limitations and blind spots inherent in traditional LiDAR setups.
Demonstrated superior performance compared to state-of-the-art methods in both benchmark and real-world evaluations.