A Study on Efficient Optimization Methods for Low-cost 3D LiDAR- based Object Detection

Recent research has focused on integrating low-cost 3D LiDAR sensors into vehicles to advance autonomous driving technologies. However, most 3D object detection algorithms are developed and validated using high-cost 3D LiDAR sensors. Therefore, this study evaluates the performance of current 3D object detection algorithms within a low-cost 3D LiDAR environment and provides a comparative analysis to identify their effectiveness.

Authors

Publication Details

Journal
Journal of Institute of Control Robotics and Systems
Published
2026-01-13
DOI
https://doi.org/10.5302/j.icros.2026.25.0210
Primary Topic
Advanced Neural Network Applications
Type
article
Field-Weighted Citation Impact
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A Study on Efficient Optimization Methods for Low-cost 3D LiDAR- based Object Detection

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A Study on Efficient Optimization Methods for Low-cost 3D LiDAR- based Object Detection

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article en

Abstract

Recent research has focused on integrating low-cost 3D LiDAR sensors into vehicles to advance autonomous driving technologies. However, most 3D object detection algorithms are developed and validated using high-cost 3D LiDAR sensors. Therefore, this study evaluates the performance of current 3D object detection algorithms within a low-cost 3D LiDAR environment and provides a comparative analysis to identify their effectiveness.

Journal of Institute of Control Robotics and SystemsVol. 32(1)
Industry, innovation and infrastructure
Openalex Percentile: Top 92%
Advanced Neural Network Applications
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