Robot Path Planning Based on Improved PRM for Wing-Box Internal Assembly

Currently, fastener installation within the narrow, confined space of a wing box must be performed manually, as existing robotic systems are unable to adequately meet the internal assembly requirements. To address this problem, a new robot with one prismatic and five revolute joints (1P5R) has been developed for entering and operating inside the wing box. Firstly, the mechanical structure and control system of the robot were designed and implemented. Then, an improved Probabilistic Roadmap (PRM) method was developed to enable rapid and smooth path planning, mainly depending on optimization of sampling strategy based on Halton sequence, an elliptical-region-based redundant point optimization strategy using control points, improving roadmap construction, and path smoothing based on B-spline curves. Finally, obstacle–avoidance path planning based on the improved PRM was simulated using the MoveIt platform, corresponding robotic motion experiments were conducted, and the improved PRM was validated.

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Publication Details

Journal
Machines
Published
2025-10-16
DOI
https://doi.org/10.3390/machines13100952
Primary Topic
Robotic Path Planning Algorithms
Type
article
Field-Weighted Citation Impact
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article

Robot Path Planning Based on Improved PRM for Wing-Box Internal Assembly

Yunbo Bi, Yu Shao, Jiefeng Jiang, Jingjing You et al.
Machines
Robotic Path Planning Algorithms
article

Robot Path Planning Based on Improved PRM for Wing-Box Internal Assembly

Yunbo Bi, Yu Shao, Jiefeng Jiang, Jingjing You, You Yong
article en

Abstract

Currently, fastener installation within the narrow, confined space of a wing box must be performed manually, as existing robotic systems are unable to adequately meet the internal assembly requirements. To address this problem, a new robot with one prismatic and five revolute joints (1P5R) has been developed for entering and operating inside the wing box. Firstly, the mechanical structure and control system of the robot were designed and implemented. Then, an improved Probabilistic Roadmap (PRM) method was developed to enable rapid and smooth path planning, mainly depending on optimization of sampling strategy based on Halton sequence, an elliptical-region-based redundant point optimization strategy using control points, improving roadmap construction, and path smoothing based on B-spline curves. Finally, obstacle–avoidance path planning based on the improved PRM was simulated using the MoveIt platform, corresponding robotic motion experiments were conducted, and the improved PRM was validated.

MachinesVol. 13(10)
Hangzhou Normal University (CN), Nanjing Forestry University (CN), Zhejiang University (CN)
Openalex Percentile: Top 71%
Robotic Path Planning Algorithms
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