Research on Robot Cleaning Path Planning of Vertical Mixing Paddle Surface

The safe removal of residual flammable contaminants from vertical mixer blades is a crucial challenge in aerospace propellant production. While robotic cleaning has become the preferred solution due to its precision and operational safety, the complex helical geometry of mixer blades presents signif...

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Main Authors: Zhouzheng Shi, Leiyang Guo, Jingde Li, Ni Cao, Xiansheng Qin, Zhanxi Wang
Format: Article
Language:English
Published: MDPI AG 2025-06-01
Series:Journal of Manufacturing and Materials Processing
Subjects:
Online Access:https://www.mdpi.com/2504-4494/9/6/198
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author Zhouzheng Shi
Leiyang Guo
Jingde Li
Ni Cao
Xiansheng Qin
Zhanxi Wang
author_facet Zhouzheng Shi
Leiyang Guo
Jingde Li
Ni Cao
Xiansheng Qin
Zhanxi Wang
author_sort Zhouzheng Shi
collection DOAJ
description The safe removal of residual flammable contaminants from vertical mixer blades is a crucial challenge in aerospace propellant production. While robotic cleaning has become the preferred solution due to its precision and operational safety, the complex helical geometry of mixer blades presents significant challenges for robotic systems, primarily in three aspects: (1) dynamic sub-region division, requiring simultaneous consideration of functional zones and residue distribution, (2) ensuring path continuity across surfaces with varying curvature, and (3) balancing time–energy efficiency in discontinuous cleaning sequences. To address these challenges, this paper proposes a novel robotic cleaning path planning method for complex curved surfaces. Firstly, we introduce a blade surface segmentation approach based on the k-means++ clustering algorithm, along with a sub-surface patch boundary determination method using parameterized curves, to achieve precise surface partitioning. Subsequently, robot cleaning paths are planned for each sub-surface according to cleaning requirements and tool constraints. Finally, with total cleaning time as the optimization objective, a genetic algorithm is employed to optimize the path combination across sub-facets. Extensive experimental results validate the effectiveness of the proposed method in robotic cleaning path planning.
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institution Kabale University
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publishDate 2025-06-01
publisher MDPI AG
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series Journal of Manufacturing and Materials Processing
spelling doaj-art-cd2977be76e040d68586a47cffb7f84a2025-08-20T03:27:40ZengMDPI AGJournal of Manufacturing and Materials Processing2504-44942025-06-019619810.3390/jmmp9060198Research on Robot Cleaning Path Planning of Vertical Mixing Paddle SurfaceZhouzheng Shi0Leiyang Guo1Jingde Li2Ni Cao3Xiansheng Qin4Zhanxi Wang5School of Mechanical Engineering, Northwestern Polytechnical University, Xi’an 710072, ChinaSchool of Mechanical Engineering, Northwestern Polytechnical University, Xi’an 710072, ChinaSchool of Mechanical Engineering, Northwestern Polytechnical University, Xi’an 710072, ChinaSchool of Mechanical Engineering, Northwestern Polytechnical University, Xi’an 710072, ChinaSchool of Mechanical Engineering, Northwestern Polytechnical University, Xi’an 710072, ChinaSchool of Mechanical Engineering, Northwestern Polytechnical University, Xi’an 710072, ChinaThe safe removal of residual flammable contaminants from vertical mixer blades is a crucial challenge in aerospace propellant production. While robotic cleaning has become the preferred solution due to its precision and operational safety, the complex helical geometry of mixer blades presents significant challenges for robotic systems, primarily in three aspects: (1) dynamic sub-region division, requiring simultaneous consideration of functional zones and residue distribution, (2) ensuring path continuity across surfaces with varying curvature, and (3) balancing time–energy efficiency in discontinuous cleaning sequences. To address these challenges, this paper proposes a novel robotic cleaning path planning method for complex curved surfaces. Firstly, we introduce a blade surface segmentation approach based on the k-means++ clustering algorithm, along with a sub-surface patch boundary determination method using parameterized curves, to achieve precise surface partitioning. Subsequently, robot cleaning paths are planned for each sub-surface according to cleaning requirements and tool constraints. Finally, with total cleaning time as the optimization objective, a genetic algorithm is employed to optimize the path combination across sub-facets. Extensive experimental results validate the effectiveness of the proposed method in robotic cleaning path planning.https://www.mdpi.com/2504-4494/9/6/198path planningrobotsurface cleaningsurface fragmentationpath combination
spellingShingle Zhouzheng Shi
Leiyang Guo
Jingde Li
Ni Cao
Xiansheng Qin
Zhanxi Wang
Research on Robot Cleaning Path Planning of Vertical Mixing Paddle Surface
Journal of Manufacturing and Materials Processing
path planning
robot
surface cleaning
surface fragmentation
path combination
title Research on Robot Cleaning Path Planning of Vertical Mixing Paddle Surface
title_full Research on Robot Cleaning Path Planning of Vertical Mixing Paddle Surface
title_fullStr Research on Robot Cleaning Path Planning of Vertical Mixing Paddle Surface
title_full_unstemmed Research on Robot Cleaning Path Planning of Vertical Mixing Paddle Surface
title_short Research on Robot Cleaning Path Planning of Vertical Mixing Paddle Surface
title_sort research on robot cleaning path planning of vertical mixing paddle surface
topic path planning
robot
surface cleaning
surface fragmentation
path combination
url https://www.mdpi.com/2504-4494/9/6/198
work_keys_str_mv AT zhouzhengshi researchonrobotcleaningpathplanningofverticalmixingpaddlesurface
AT leiyangguo researchonrobotcleaningpathplanningofverticalmixingpaddlesurface
AT jingdeli researchonrobotcleaningpathplanningofverticalmixingpaddlesurface
AT nicao researchonrobotcleaningpathplanningofverticalmixingpaddlesurface
AT xianshengqin researchonrobotcleaningpathplanningofverticalmixingpaddlesurface
AT zhanxiwang researchonrobotcleaningpathplanningofverticalmixingpaddlesurface