基于复杂网络的管道巡检机器人路径规划方法

Path Planning Method for Pipeline Inspection Robots Based on Complex Networks

摘要: 管道内巡检机器人的路径规划是降低巡检能耗与时间成本的关键环节。为解决管道全覆盖巡检问题，文章提出了一种基于经典中国邮递员问题(CPP)框架的系统性工程解决方案。该方法首先将管道结构抽象为复杂网络模型，随后提取其最小生成树以获取网络的最优连通骨架。在此基础上，针对原始网络图进行欧拉化改造，通过匹配奇度节点并添加权值最小的重复边，将非欧拉图转化为欧拉图。最终引入Hierholzer算法求解欧拉回路，生成一条能够无遗漏覆盖所有管道且总权值最小的巡检路径。实验结果表明，与传统路径规划策略相比，该方法显著提升了巡检机器人的路径利用率与运行性能，为管道巡检任务提供了一种高效、可行的技术方案。

Abstract: Path planning for in-pipe inspection robots is a key technology for reducing energy consumption and time costs during inspection tasks. To address the full coverage inspection problem in pipelines, this paper presents a systematic engineering solution based on the classic Chinese Postman Problem (CPP) framework. In this approach, the pipeline structure is first modeled as a complex network. The minimum spanning tree of the network is then extracted to obtain the optimal connected backbone. Based on this, an Eulerian transformation is applied to the original network graph: by matching odd-degree nodes and adding minimal-weight duplicated edges, the non-Eulerian graph is converted into an Eulerian graph. Finally, the Hierholzer algorithm is employed to find an Eulerian circuit, generating an inspection route that covers all pipeline segments without omission and minimizes total weight. Experimental results demonstrate that, compared with traditional methods, the proposed solution significantly enhances path efficiency and operational performance of inspection robots, offering an effective and feasible technical solution for pipeline inspection applications.