Academic Journal
Spatial path planning for hydraulic turbine flow channels using an improved RRT algorithm.
| Τίτλος: | Spatial path planning for hydraulic turbine flow channels using an improved RRT algorithm. |
|---|---|
| Συγγραφείς: | Xu, Xiangqian1 (AUTHOR) xqxu@xsyu.edu.cn, Suo, Yang1 (AUTHOR) 23211050712@stumail.xsyu.edu.cn |
| Πηγή: | Robotic Intelligence & Automation (RIA). 2026, Vol. 46 Issue 4, p502-515. 14p. |
| Θεματικοί όροι: | *Industrial robots, *Nondestructive testing, Robotic path planning, Hydraulic turbines, Cameras |
| Περίληψη: | Purpose: The purpose of this study is to propose a path planning method based on an improved Rapidly-exploring Random Tree (RRT) algorithm to address the path planning challenges of robotic arms carrying inspection cameras in the complex and narrow flow channel spaces of hydraulic turbines. Design/methodology/approach: An improved RRT algorithm is developed, optimizing the tree expansion process by adopting a direction-guided strategy and adaptive step size adjustment. A probabilistic bias sampling factor is introduced to enhance the expansion direction and efficiency. Redundant points are removed using a stepwise checking method, and the inspection path is smoothed with Bézier curves. Simulation experiments are conducted in MATLAB using a 3D model of the turbine flow channel. Findings: The improved RRT algorithm reduces computation time by 88% compared to RRT-Connect and RRT-Extend, and is 71.6% faster than RRT-star. The path length is 97.89% shorter than RRT-Connect, 95.93% shorter than RRT-Extend and 80.89% fewer than RRT-star. The number of path nodes is 97.1% fewer than RRT-Connect, 97.6% fewer than RRT-Extend and 94% fewer than RRT-star. The algorithm achieves a 100% success rate, outperforming traditional path planning algorithms in overall performance. Practical implications: The improved RRT algorithm provides an efficient and feasible solution for robotic path planning in hydraulic turbine defect inspection, significantly reducing computation time and path length. Originality/value: The proposed improved RRT algorithm significantly enhances the efficiency and quality of path planning for robotic arms in narrow flow channel environments, offering a high-performance path planning solution for robotic defect inspection and applications. [ABSTRACT FROM AUTHOR] |
| Copyright of Robotic Intelligence & Automation (RIA) is the property of Emerald Publishing Limited 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.) | |
| Βάση Δεδομένων: | Business Source Index |
| FullText | Text: Availability: 0 |
|---|---|
| Header | DbId: bsx DbLabel: Business Source Index An: 195463395 RelevancyScore: 1412 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 1411.61413574219 |
| IllustrationInfo | |
| Items | – Name: Title Label: Title Group: Ti Data: Spatial path planning for hydraulic turbine flow channels using an improved RRT algorithm. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Xu%2C+Xiangqian%22">Xu, Xiangqian</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> xqxu@xsyu.edu.cn</i><br /><searchLink fieldCode="AR" term="%22Suo%2C+Yang%22">Suo, Yang</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> 23211050712@stumail.xsyu.edu.cn</i> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Robotic+Intelligence+%26+Automation+%28RIA%29%22">Robotic Intelligence & Automation (RIA)</searchLink>. 2026, Vol. 46 Issue 4, p502-515. 14p. – Name: Subject Label: Subject Terms Group: Su Data: *<searchLink fieldCode="DE" term="%22Industrial+robots%22">Industrial robots</searchLink><br />*<searchLink fieldCode="DE" term="%22Nondestructive+testing%22">Nondestructive testing</searchLink><br /><searchLink fieldCode="DE" term="%22Robotic+path+planning%22">Robotic path planning</searchLink><br /><searchLink fieldCode="DE" term="%22Hydraulic+turbines%22">Hydraulic turbines</searchLink><br /><searchLink fieldCode="DE" term="%22Cameras%22">Cameras</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Purpose: The purpose of this study is to propose a path planning method based on an improved Rapidly-exploring Random Tree (RRT) algorithm to address the path planning challenges of robotic arms carrying inspection cameras in the complex and narrow flow channel spaces of hydraulic turbines. Design/methodology/approach: An improved RRT algorithm is developed, optimizing the tree expansion process by adopting a direction-guided strategy and adaptive step size adjustment. A probabilistic bias sampling factor is introduced to enhance the expansion direction and efficiency. Redundant points are removed using a stepwise checking method, and the inspection path is smoothed with Bézier curves. Simulation experiments are conducted in MATLAB using a 3D model of the turbine flow channel. Findings: The improved RRT algorithm reduces computation time by 88% compared to RRT-Connect and RRT-Extend, and is 71.6% faster than RRT-star. The path length is 97.89% shorter than RRT-Connect, 95.93% shorter than RRT-Extend and 80.89% fewer than RRT-star. The number of path nodes is 97.1% fewer than RRT-Connect, 97.6% fewer than RRT-Extend and 94% fewer than RRT-star. The algorithm achieves a 100% success rate, outperforming traditional path planning algorithms in overall performance. Practical implications: The improved RRT algorithm provides an efficient and feasible solution for robotic path planning in hydraulic turbine defect inspection, significantly reducing computation time and path length. Originality/value: The proposed improved RRT algorithm significantly enhances the efficiency and quality of path planning for robotic arms in narrow flow channel environments, offering a high-performance path planning solution for robotic defect inspection and applications. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Robotic Intelligence & Automation (RIA) is the property of Emerald Publishing Limited 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.) |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=bsx&AN=195463395 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1108/RIA-07-2025-0214 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 14 StartPage: 502 Subjects: – SubjectFull: Industrial robots Type: general – SubjectFull: Nondestructive testing Type: general – SubjectFull: Robotic path planning Type: general – SubjectFull: Hydraulic turbines Type: general – SubjectFull: Cameras Type: general Titles: – TitleFull: Spatial path planning for hydraulic turbine flow channels using an improved RRT algorithm. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Xu, Xiangqian – PersonEntity: Name: NameFull: Suo, Yang IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 07 Text: 2026 Type: published Y: 2026 Identifiers: – Type: issn-print Value: 27546969 Numbering: – Type: volume Value: 46 – Type: issue Value: 4 Titles: – TitleFull: Robotic Intelligence & Automation (RIA) Type: main |
| ResultId | 1 |