IFA-ICP: A Low-Complexity and Image Feature-Assisted Iterative Closest Point (ICP) Scheme for Odometry Estimation in SLAM, and Its FPGA-Based Hardware Accelerator Design

Jia-En Li, Yin-Tsung Hwang

Open source

DOI: 10.3390/s26082326
Published: 2026-04-09
Container: Sensors
Publisher: MDPI AG
Open access: unknown

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Cite this work

BibTeX

@article{allodium:10.3390/s26082326,
  title = {IFA-ICP: A Low-Complexity and Image Feature-Assisted Iterative Closest Point (ICP) Scheme for Odometry Estimation in SLAM, and Its FPGA-Based Hardware Accelerator Design},
  author = {Jia-En Li and Yin-Tsung Hwang},
  year = {2026},
  journal = {Sensors},
  doi = {10.3390/s26082326},
  url = {https://doi.org/10.3390/s26082326}
}

RIS

TY  - JOUR
TI  - IFA-ICP: A Low-Complexity and Image Feature-Assisted Iterative Closest Point (ICP) Scheme for Odometry Estimation in SLAM, and Its FPGA-Based Hardware Accelerator Design
AU  - Jia-En Li
AU  - Yin-Tsung Hwang
PY  - 2026
JO  - Sensors
DO  - 10.3390/s26082326
UR  - https://doi.org/10.3390/s26082326
ER  -

APA

Li, J., & Hwang, Y. (2026). IFA-ICP: A Low-Complexity and Image Feature-Assisted Iterative Closest Point (ICP) Scheme for Odometry Estimation in SLAM, and Its FPGA-Based Hardware Accelerator Design. Sensors. https://doi.org/10.3390/s26082326

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crossref · retrieved 2026-11-10T07:52:14.992Z