Research on Automatic Assembling Method of Large Parts of Spacecraft Based on Vision Guidance

Zhang, Man; Zhang, Chengcheng; Wang, Wei; Du, Ruizhao; Meng, Shaohua

doi:10.1145/3469213.3470354

Cited by 1 publication

(2 citation statements)

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“…During evolution, once the historical best 𝑣𝑝 𝑞 | 𝑤 of any component is reset due to the generation of a child 𝑣𝑝, the pose feasible region update can be selectively started according to the change in the 𝑣𝑝 𝑞 . ℱ 𝑖+1 is updated from ℱ 𝑖 , and the update work can be summarized into four steps, including the following: (a) simplifying 𝒙 𝑤 based on structural stability to obtain 𝒙 𝑤′ , 𝒙 ′ ; (b) determining 𝛿 𝑖+1 and 𝐹 𝑖+1 𝛿 𝑖+1 ,𝑊 and selecting the support 𝑣𝑝 according to 𝑣𝑝 𝑞 from {𝒫 𝑖 , 𝒞 𝑖 }; (c) calculating the projection of the support 𝑣𝑝 to the boundary by Formulas ( 6)- (9); and (d) solving the optimization problem (10) and performing affinity-based interpolation with ( 11)-(13).…”

Section: Sparse Trajectory Approximationmentioning

confidence: 99%

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A Learnable Viewpoint Evolution Method for Accurate Pose Estimation of Complex Assembled Product

Zhao,

Kong,

2024

Applied Sciences

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Balancing adaptability, reliability, and accuracy in vision technology has always been a major bottleneck limiting its application in appearance assurance for complex objects in high-end equipment production. Data-driven deep learning shows robustness to feature diversity but is limited by interpretability and accuracy. The traditional vision scheme is reliable and can achieve high accuracy, but its adaptability is insufficient. The deeper reason is the lack of appropriate architecture and integration strategies between the learning paradigm and empirical design. To this end, a learnable viewpoint evolution algorithm for high-accuracy pose estimation of complex assembled products under free view is proposed. To alleviate the balance problem of exploration and optimization in estimation, shape-constrained virtual–real matching, evolvable feasible region, and specialized population migration and reproduction strategies are designed. Furthermore, a learnable evolution control mechanism is proposed, which integrates a guided model based on experience and is cyclic-trained with automatically generated effective trajectories to improve the evolution process. Compared to the m of the state-of-the-art data-driven method and the m of the classic strategy combination, the pose estimation error of complex assembled product in this study is m, which proves the effectiveness of the proposed method. Meanwhile, through in-depth exploration, the robustness, parameter sensitivity, and adaptability to the virtual–real appearance variations are sequentially verified.

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Section: Sparse Trajectory Approximationmentioning

confidence: 99%

“…Technically, camera pose estimation focused in this study is the absolute pose estimation (APE). Research in this direction mainly includes six categories [7][8][9]:…”

Section: Introductionmentioning

confidence: 99%

A Learnable Viewpoint Evolution Method for Accurate Pose Estimation of Complex Assembled Product

Zhao,

Kong,

2024

Applied Sciences

View full text Add to dashboard Cite

show abstract

Research on Automatic Assembling Method of Large Parts of Spacecraft Based on Vision Guidance

Cited by 1 publication

References 2 publications

A Learnable Viewpoint Evolution Method for Accurate Pose Estimation of Complex Assembled Product

A Learnable Viewpoint Evolution Method for Accurate Pose Estimation of Complex Assembled Product

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