Spatial layout planning of cable based on a hybrid method combining interference obstacle local post-insertion and improved Dubins curves

Cables in three-dimensional (3D) wall-adherent routing must simultaneously satisfy terminal direction vectors and bending curvature constraints, making forward design and precise pre-cutting a significant challenge. To address this, this paper proposes a hybrid planning method, termed IOLPDC, which combines interference obstacle local post-insertion with improved Dubins curves. The approach first utilizes an undirected graph spanning tree to unfold the 3D routing environment into a two-dimensional (2D) plane. Within this 2D domain, a multi-waypoint Dubins curve is introduced, and a post-insertion strategy is developed. This strategy generates a highly efficient Dubins path by initially ignoring obstacles, followed by binary-tree detouring, pruning, and redundant waypoint elimination to achieve a high-quality feasible path satisfying both directional and curvature constraints. Additionally, for local non-wall-adherent regions arising during 3D reconstruction, an engineering transition solver based on a 3D Dubins path is implemented via a Differential Evolution algorithm. Simulation results in a planar environment demonstrate that compared with Hybrid A* and RRT*Dubins, the proposed IOLPDC method reduces path length by 13.23% and 8.51%, and shortens median planning time by 50.00% and 34.38%, respectively. Experimental verification confirms that cables pre-cut according to the planned lengths precisely match the actual routed paths, effectively eliminating the traditional “cut-to-fit” process and demonstrating strong engineering practicality.

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Publication Details

Journal
PLoS ONE
Published
2026-10-05
DOI
https://doi.org/10.1371/journal.pone.0359351
Primary Topic
Robotic Path Planning Algorithms
Type
article
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article

Spatial layout planning of cable based on a hybrid method combining interference obstacle local post-insertion and improved Dubins curves

Songkai Liu, Chao Kang, Xiaoyang Zhang, Bing Cai et al.
PLoS ONE
Robotic Path Planning Algorithms
article

Spatial layout planning of cable based on a hybrid method combining interference obstacle local post-insertion and improved Dubins curves

Songkai Liu, Chao Kang, Xiaoyang Zhang, Bing Cai, Bo Deng, Zhigang Xu
article en

Abstract

Cables in three-dimensional (3D) wall-adherent routing must simultaneously satisfy terminal direction vectors and bending curvature constraints, making forward design and precise pre-cutting a significant challenge. To address this, this paper proposes a hybrid planning method, termed IOLPDC, which combines interference obstacle local post-insertion with improved Dubins curves. The approach first utilizes an undirected graph spanning tree to unfold the 3D routing environment into a two-dimensional (2D) plane. Within this 2D domain, a multi-waypoint Dubins curve is introduced, and a post-insertion strategy is developed. This strategy generates a highly efficient Dubins path by initially ignoring obstacles, followed by binary-tree detouring, pruning, and redundant waypoint elimination to achieve a high-quality feasible path satisfying both directional and curvature constraints. Additionally, for local non-wall-adherent regions arising during 3D reconstruction, an engineering transition solver based on a 3D Dubins path is implemented via a Differential Evolution algorithm. Simulation results in a planar environment demonstrate that compared with Hybrid A* and RRT*Dubins, the proposed IOLPDC method reduces path length by 13.23% and 8.51%, and shortens median planning time by 50.00% and 34.38%, respectively. Experimental verification confirms that cables pre-cut according to the planned lengths precisely match the actual routed paths, effectively eliminating the traditional “cut-to-fit” process and demonstrating strong engineering practicality.

PLoS ONEVol. 21(10)
Shenyang Institute of Automation (CN), Chinese Academy of Sciences (CN), Jiangsu University of Science and Technology (CN), University of Chinese Academy of Sciences (CN)
Openalex Percentile: Top 14%
Robotic Path Planning Algorithms
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