A Probabilistic Formulation of LiDAR Mapping With Neural Radiance Fields

Matthew McDermott; Jason Rife

doi:10.1109/lra.2025.3557301

ScienceGate Book Chapters

JOURNAL ARTICLE

A Probabilistic Formulation of LiDAR Mapping With Neural Radiance Fields

Matthew McDermott Jason Rife

Year: 2025 Journal: IEEE Robotics and Automation Letters Vol: 10 (6)Pages: 5409-5416 Publisher: Institute of Electrical and Electronics Engineers

DOI: 10.1109/lra.2025.3557301

Get Full-Text PDF Get Analytical Report

Keywords:

Radiance Lidar Probabilistic logic Remote sensing Artificial neural network Computer science Geography Artificial intelligence Environmental science

Metrics

Cited By

13.86

FWCI (Field Weighted Citation Impact)

Refs

0.96

Citation Normalized Percentile

Is in top 1%

Is in top 10%

Citation History

Topics

Robotics and Sensor-Based Localization

Physical Sciences → Engineering → Aerospace Engineering

Advanced Vision and Imaging

Physical Sciences → Computer Science → Computer Vision and Pattern Recognition

Remote Sensing and LiDAR Applications

Physical Sciences → Environmental Science → Environmental Engineering

A Probabilistic Formulation of LiDAR Mapping With Neural Radiance Fields

Metrics

Citation History

Topics

Related Documents

Neural Radiance Fields with LiDAR Maps

Camera-Lidar Consistent Neural Radiance Fields

NeRF-LiDAR: Generating Realistic LiDAR Point Clouds with Neural Radiance Fields

LiDAR-NeRF: Novel LiDAR View Synthesis via Neural Radiance Fields

SiLVR: Scalable Lidar-Visual Reconstruction with Neural Radiance Fields for Robotic Inspection