Resource-Exploration-Oriented Lunar Rocks Monocular Detection and 3D Pose Estimation

Lunar in situ resource utilization is a core goal in lunar exploration, with accurate lunar rock pose estimation being essential. To address the challenges posed by the lack of texture features and extreme lighting conditions, this study proposes the Simulation-YOLO-Hourglass-Transformer (SYHT) meth...

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Main Authors: Jiayu Suo, Hongfeng Long, Yuebo Ma, Yuhao Zhang, Zhen Liang, Chuan Yan, Rujin Zhao
Format: Article
Language:English
Published: MDPI AG 2024-12-01
Series:Aerospace
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Online Access:https://www.mdpi.com/2226-4310/12/1/4
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author Jiayu Suo
Hongfeng Long
Yuebo Ma
Yuhao Zhang
Zhen Liang
Chuan Yan
Rujin Zhao
author_facet Jiayu Suo
Hongfeng Long
Yuebo Ma
Yuhao Zhang
Zhen Liang
Chuan Yan
Rujin Zhao
author_sort Jiayu Suo
collection DOAJ
description Lunar in situ resource utilization is a core goal in lunar exploration, with accurate lunar rock pose estimation being essential. To address the challenges posed by the lack of texture features and extreme lighting conditions, this study proposes the Simulation-YOLO-Hourglass-Transformer (SYHT) method. The method enhances accuracy and robustness in complex lunar environments, demonstrating strong adaptability and excellent performance, particularly in conditions of extreme lighting and scarce texture. This approach provides valuable insights for object pose estimation in lunar exploration tasks and lays the foundation for lunar resource development. First, the YOLO-Hourglass-Transformer (YHT) network is used to extract keypoint information from each rock and generate the corresponding 3D pose. Then, a lunar surface imaging physics simulation model is employed to generate simulated lunar rock data for testing the method. The experimental results show that the SYHT method performs exceptionally well on simulated lunar rock data, achieving a mean per-joint position error (MPJPE) of 37.93 mm and a percentage of correct keypoints (PCK) of 99.94%, significantly outperforming existing methods. Finally, transfer learning experiments on real-world datasets validate its strong generalization capability, highlighting its effectiveness for lunar rock pose estimation in both simulated and real lunar environments.
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institution Kabale University
issn 2226-4310
language English
publishDate 2024-12-01
publisher MDPI AG
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series Aerospace
spelling doaj-art-bc53c97660f24bf8885ff7aed6faf0a22025-01-24T13:15:24ZengMDPI AGAerospace2226-43102024-12-01121410.3390/aerospace12010004Resource-Exploration-Oriented Lunar Rocks Monocular Detection and 3D Pose EstimationJiayu Suo0Hongfeng Long1Yuebo Ma2Yuhao Zhang3Zhen Liang4Chuan Yan5Rujin Zhao6Institute of Optics and Electronics of Chinese Academy of Sciences, Chengdu 610209, ChinaInstitute of Optics and Electronics of Chinese Academy of Sciences, Chengdu 610209, ChinaInstitute of Optics and Electronics of Chinese Academy of Sciences, Chengdu 610209, ChinaInstitute of Optics and Electronics of Chinese Academy of Sciences, Chengdu 610209, ChinaInstitute of Optics and Electronics of Chinese Academy of Sciences, Chengdu 610209, ChinaInstitute of Optics and Electronics of Chinese Academy of Sciences, Chengdu 610209, ChinaInstitute of Optics and Electronics of Chinese Academy of Sciences, Chengdu 610209, ChinaLunar in situ resource utilization is a core goal in lunar exploration, with accurate lunar rock pose estimation being essential. To address the challenges posed by the lack of texture features and extreme lighting conditions, this study proposes the Simulation-YOLO-Hourglass-Transformer (SYHT) method. The method enhances accuracy and robustness in complex lunar environments, demonstrating strong adaptability and excellent performance, particularly in conditions of extreme lighting and scarce texture. This approach provides valuable insights for object pose estimation in lunar exploration tasks and lays the foundation for lunar resource development. First, the YOLO-Hourglass-Transformer (YHT) network is used to extract keypoint information from each rock and generate the corresponding 3D pose. Then, a lunar surface imaging physics simulation model is employed to generate simulated lunar rock data for testing the method. The experimental results show that the SYHT method performs exceptionally well on simulated lunar rock data, achieving a mean per-joint position error (MPJPE) of 37.93 mm and a percentage of correct keypoints (PCK) of 99.94%, significantly outperforming existing methods. Finally, transfer learning experiments on real-world datasets validate its strong generalization capability, highlighting its effectiveness for lunar rock pose estimation in both simulated and real lunar environments.https://www.mdpi.com/2226-4310/12/1/4pose estimationlunar exploration applicationstransformer-based architecturespatial feature extractionsimulation-YOLO-hourglass-transformer
spellingShingle Jiayu Suo
Hongfeng Long
Yuebo Ma
Yuhao Zhang
Zhen Liang
Chuan Yan
Rujin Zhao
Resource-Exploration-Oriented Lunar Rocks Monocular Detection and 3D Pose Estimation
Aerospace
pose estimation
lunar exploration applications
transformer-based architecture
spatial feature extraction
simulation-YOLO-hourglass-transformer
title Resource-Exploration-Oriented Lunar Rocks Monocular Detection and 3D Pose Estimation
title_full Resource-Exploration-Oriented Lunar Rocks Monocular Detection and 3D Pose Estimation
title_fullStr Resource-Exploration-Oriented Lunar Rocks Monocular Detection and 3D Pose Estimation
title_full_unstemmed Resource-Exploration-Oriented Lunar Rocks Monocular Detection and 3D Pose Estimation
title_short Resource-Exploration-Oriented Lunar Rocks Monocular Detection and 3D Pose Estimation
title_sort resource exploration oriented lunar rocks monocular detection and 3d pose estimation
topic pose estimation
lunar exploration applications
transformer-based architecture
spatial feature extraction
simulation-YOLO-hourglass-transformer
url https://www.mdpi.com/2226-4310/12/1/4
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AT yuhaozhang resourceexplorationorientedlunarrocksmonoculardetectionand3dposeestimation
AT zhenliang resourceexplorationorientedlunarrocksmonoculardetectionand3dposeestimation
AT chuanyan resourceexplorationorientedlunarrocksmonoculardetectionand3dposeestimation
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