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.
- DOI
- 10.3390/s26082326
- Published
- 2026 Apr 9
- Container
- Sensors (Basel, Switzerland)
- Publisher
- Not recorded
- Open access
- yes
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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 = {Li JE and Hwang YT},
year = {2026},
journal = {Sensors (Basel, Switzerland)},
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 - Li JE AU - Hwang YT PY - 2026 JO - Sensors (Basel, Switzerland) DO - 10.3390/s26082326 UR - https://doi.org/10.3390/s26082326 ER -
APA
JE, L., & YT, H. (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 (Basel, Switzerland). https://doi.org/10.3390/s26082326
Source records
- pubmed · retrieved 2026-09-24T23:52:06.253Z