Estimation of Virtual Moon Surface using LiDAR Measurements

In this work, we present the MLS (Moon Lidar Simulation) system—a terrain height map and normal map prediction system for virtual lunar landscapes that uses LiDAR point cloud data as input. When operating the MLS system, we first simulate a virtual LiDAR sensor to sample height information from a 3D terrain and preprocess the data to generate an initial height map. We then leverage a Masked Autoencoder (MAE) structure to predict a normal map based on the height map input. Our system demonstrates its capability to predict occluded terrain areas, and we visualize the resulting height map and normal map in the Unity game engine.

Authors

Publication Details

Journal
Journal of the Korea Computer Graphics Society
Published
2025-03-01
DOI
https://doi.org/10.15701/kcgs.2025.31.1.1
Primary Topic
Robotics and Sensor-Based Localization
Type
article
Field-Weighted Citation Impact
0.00

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article

Estimation of Virtual Moon Surface using LiDAR Measurements

Myeung Un Kim, Choongho Chung, Sung‐Hee Lee, Dae-Kwan Kim et al.
Journal of the Korea Computer Graphics Society
Robotics and Sensor-Based Localization
article

Estimation of Virtual Moon Surface using LiDAR Measurements

Myeung Un Kim, Choongho Chung, Sung‐Hee Lee, Dae-Kwan Kim, Mingi Yeom
article en

Abstract

In this work, we present the MLS (Moon Lidar Simulation) system—a terrain height map and normal map prediction system for virtual lunar landscapes that uses LiDAR point cloud data as input. When operating the MLS system, we first simulate a virtual LiDAR sensor to sample height information from a 3D terrain and preprocess the data to generate an initial height map. We then leverage a Masked Autoencoder (MAE) structure to predict a normal map based on the height map input. Our system demonstrates its capability to predict occluded terrain areas, and we visualize the resulting height map and normal map in the Unity game engine.

Journal of the Korea Computer Graphics SocietyVol. 31(1)
Korea Aerospace Research Institute, National Research Foundation of Korea
Openalex Percentile: Top 94%
Robotics and Sensor-Based Localization
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