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
- Chang Mook Kang (ORCID: https://orcid.org/0000-0003-2467-2074)
- Junhyeong Kim (ORCID: https://orcid.org/0000-0003-1768-5360)
- Minchang Kim
- Haneul Jang
- Doseon Kim
- Taewoong Kim
- Hyungjun Park
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
- 0.00