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Robust Pose Estimation for Noncooperative Spacecraft Under Rapid Inter-Frame Motion: A Two-Stage Point Cloud Registration Approach.

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Title: Robust Pose Estimation for Noncooperative Spacecraft Under Rapid Inter-Frame Motion: A Two-Stage Point Cloud Registration Approach.
Authors: Zhao, Mingyuan1,2 (AUTHOR), Xu, Long2,3 (AUTHOR) lxu@nao.cas.cn
Source: Remote Sensing. Jun2025, Vol. 17 Issue 11, p1944. 21p.
Subjects: Point cloud, Relative motion, Bathymetry, Space vehicles, Statistical sampling
Abstract: This paper addresses the challenge of robust pose estimation for spacecraft under rapid inter-frame motion, proposing a two-stage point cloud registration framework. The first stage computes coarse pose estimation by leveraging Fast Point Feature Histogram (FPFH) descriptors with random sample and consensus (RANSAC) for correspondence matching, effectively handling significant positional displacements. The second stage refines the solution through geometry-aware fine registration using raw point cloud data, enhancing precision through a multi-scale iterative ICP-like framework. To validate the approach, we simulate time-of-flight (ToF) sensor measurements by rendering NASA's public 3D spacecraft models and obtain 3D point clouds by back-projecting the depth measurements to 3D space. Comprehensive experiments demonstrate superior performance over several state-of-the-art methods in both accuracy and robustness under rapid inter-frame motion scenarios. The dual-stage architecture proves effective in maintaining tracking continuity while mitigating error accumulation from fast relative motion, showing promise for autonomous spacecraft proximity operations. [ABSTRACT FROM AUTHOR]
Copyright of Remote Sensing is the property of MDPI and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: Robust Pose Estimation for Noncooperative Spacecraft Under Rapid Inter-Frame Motion: A Two-Stage Point Cloud Registration Approach.
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  Data: <searchLink fieldCode="AR" term="%22Zhao%2C+Mingyuan%22">Zhao, Mingyuan</searchLink><relatesTo>1,2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Xu%2C+Long%22">Xu, Long</searchLink><relatesTo>2,3</relatesTo> (AUTHOR)<i> lxu@nao.cas.cn</i>
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  Data: <searchLink fieldCode="JN" term="%22Remote+Sensing%22">Remote Sensing</searchLink>. Jun2025, Vol. 17 Issue 11, p1944. 21p.
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  Data: <searchLink fieldCode="DE" term="%22Point+cloud%22">Point cloud</searchLink><br /><searchLink fieldCode="DE" term="%22Relative+motion%22">Relative motion</searchLink><br /><searchLink fieldCode="DE" term="%22Bathymetry%22">Bathymetry</searchLink><br /><searchLink fieldCode="DE" term="%22Space+vehicles%22">Space vehicles</searchLink><br /><searchLink fieldCode="DE" term="%22Statistical+sampling%22">Statistical sampling</searchLink>
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  Label: Abstract
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  Data: This paper addresses the challenge of robust pose estimation for spacecraft under rapid inter-frame motion, proposing a two-stage point cloud registration framework. The first stage computes coarse pose estimation by leveraging Fast Point Feature Histogram (FPFH) descriptors with random sample and consensus (RANSAC) for correspondence matching, effectively handling significant positional displacements. The second stage refines the solution through geometry-aware fine registration using raw point cloud data, enhancing precision through a multi-scale iterative ICP-like framework. To validate the approach, we simulate time-of-flight (ToF) sensor measurements by rendering NASA's public 3D spacecraft models and obtain 3D point clouds by back-projecting the depth measurements to 3D space. Comprehensive experiments demonstrate superior performance over several state-of-the-art methods in both accuracy and robustness under rapid inter-frame motion scenarios. The dual-stage architecture proves effective in maintaining tracking continuity while mitigating error accumulation from fast relative motion, showing promise for autonomous spacecraft proximity operations. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Remote Sensing is the property of MDPI and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.3390/rs17111944
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      – Code: eng
        Text: English
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        PageCount: 21
        StartPage: 1944
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      – SubjectFull: Point cloud
        Type: general
      – SubjectFull: Relative motion
        Type: general
      – SubjectFull: Bathymetry
        Type: general
      – SubjectFull: Space vehicles
        Type: general
      – SubjectFull: Statistical sampling
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      – TitleFull: Robust Pose Estimation for Noncooperative Spacecraft Under Rapid Inter-Frame Motion: A Two-Stage Point Cloud Registration Approach.
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              Text: Jun2025
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