αLiDAR: An Adaptive High-Resolution Panoramic LiDAR System

LiDAR technology holds vast potential across various sectors, including robotics, autonomous driving, and urban planning. However, the performance of current LiDAR sensors is hindered by limited field of view (FOV), low resolution, and lack of flexible focusing capability. We introduce αLiDAR, an innovative LiDAR system that employs controllable actuation to provide a panoramic FOV, high resolution, and adaptable scanning focus. The core concept of αLiDAR is to expand the operational freedom of a LiDAR sensor through the incorporation of a controllable, active rotational mechanism. This modification allows the sensor to scan previously inaccessible blind spots and focus on specific areas of interest in an adaptive manner. By modeling uncertainties in LiDAR rotation process and estimating point-wise uncertainty, αLiDAR can correct point cloud distortions resulted from significant rotation. In addition, by optimizing LiDAR's rotation trajectory, αLiDAR can swiftly adapt to dynamic areas of interest. We developed several prototypes of αLiDAR and conducted comprehensive evaluations in various indoor and outdoor real-world scenarios. Our results demonstrate that αLiDAR achieves centimeter-level pose estimation accuracy, with an average latency of only 37 ms. In two typical LiDAR applications, αLiDAR significantly enhances 3D mapping accuracy, coverage, and density by 8.5×, 2×, and 1.6× respectively, compared to conventional LiDAR sensors. Additionally, αLiDAR's adaptive rotation improves the effective sensing distance by 1.8× and increases the number of perceived objects by 1.9×. A video demonstration of αLiDAR's in action in real world is available at https://youtu.be/x4zc_I_xTaw. The code is available at https://github.com/HViktorTsoi/alpha_lidar.

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Publication Details

Published
2024-12-04
DOI
https://doi.org/10.1145/3636534.3690708
Citations
6
Primary Topic
Robotics and Sensor-Based Localization
Type
article
Field-Weighted Citation Impact
7.79
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article

αLiDAR: An Adaptive High-Resolution Panoramic LiDAR System

Jiahe Cui, Jianwei Niu, Yuze He, Guoliang Xing et al.
6 citations
Robotics and Sensor-Based Localization
7.79
article

αLiDAR: An Adaptive High-Resolution Panoramic LiDAR System

Jiahe Cui, Jianwei Niu, Yuze He, Guoliang Xing, Zhenchao Ouyang
article en
6 citations

Abstract

LiDAR technology holds vast potential across various sectors, including robotics, autonomous driving, and urban planning. However, the performance of current LiDAR sensors is hindered by limited field of view (FOV), low resolution, and lack of flexible focusing capability. We introduce αLiDAR, an innovative LiDAR system that employs controllable actuation to provide a panoramic FOV, high resolution, and adaptable scanning focus. The core concept of αLiDAR is to expand the operational freedom of a LiDAR sensor through the incorporation of a controllable, active rotational mechanism. This modification allows the sensor to scan previously inaccessible blind spots and focus on specific areas of interest in an adaptive manner. By modeling uncertainties in LiDAR rotation process and estimating point-wise uncertainty, αLiDAR can correct point cloud distortions resulted from significant rotation. In addition, by optimizing LiDAR's rotation trajectory, αLiDAR can swiftly adapt to dynamic areas of interest. We developed several prototypes of αLiDAR and conducted comprehensive evaluations in various indoor and outdoor real-world scenarios. Our results demonstrate that αLiDAR achieves centimeter-level pose estimation accuracy, with an average latency of only 37 ms. In two typical LiDAR applications, αLiDAR significantly enhances 3D mapping accuracy, coverage, and density by 8.5×, 2×, and 1.6× respectively, compared to conventional LiDAR sensors. Additionally, αLiDAR's adaptive rotation improves the effective sensing distance by 1.8× and increases the number of perceived objects by 1.9×. A video demonstration of αLiDAR's in action in real world is available at https://youtu.be/x4zc_I_xTaw. The code is available at https://github.com/HViktorTsoi/alpha_lidar.

Chinese University of Hong Kong (HK), Beihang University (CN)
Affordable and clean energy
Openalex Percentile: Top 3%
Robotics and Sensor-Based Localization
7.79
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