GPU-Accelerated 3D Normal Distributions Transform
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- Nguyen Anh
- Graduate School of Informatics, Nagoya University
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- Cano Abraham Monrroy
- MAP IV, Inc.
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- Edahiro Masato
- Graduate School of Informatics, Nagoya University
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- Kato Shinpei
- Department of Computer Science, Graduate School of Information Science and Technology, The University of Tokyo
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Abstract
<p>The three-dimensional (3D) normal distributions transform (NDT) is a popular scan registration method for 3D point cloud datasets. It has been widely used in sensor-based localization and mapping applications. However, the NDT cannot entirely utilize the computing power of modern many-core processors, such as graphics processing units (GPUs), because of the NDT’s linear nature. In this study, we investigated the use of NVIDIA’s GPUs and their programming platform called compute unified device architecture (CUDA) to accelerate the NDT algorithm. We proposed a design and implementation of our GPU-accelerated 3D NDT (GPU NDT). Our methods can achieve a speedup rate of up to 34 times, compared with the NDT implemented in the point cloud library (PCL).</p>
Journal
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- Journal of Robotics and Mechatronics
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Journal of Robotics and Mechatronics 35 (2), 445-459, 2023-04-20
Fuji Technology Press Ltd.
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Details 詳細情報について
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- CRID
- 1390295823371121920
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- NII Book ID
- AA10809998
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- ISSN
- 18838049
- 09153942
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- NDL BIB ID
- 032772306
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- Text Lang
- en
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- Data Source
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- JaLC
- NDL
- Crossref
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- Abstract License Flag
- Disallowed