提出分层启发式方法，高效计算平面中避障的多组不重叠斯坦纳树。
A Hierarchical Heuristic for Clustered Steiner Trees in the Plane with Obstacles
- 采用分层结构结合捆绑操作，分步构建多组互不重叠的斯坦纳树。
- 在凸与非凸障碍物场景下均实现高效求解，避免网络重叠与杂乱。
- 适用于受限二维空间中多智能体分布式协同建模，适合路径规划研究者。
欧几里得斯坦纳树广泛应用于真实世界中最小网络建模。本文研究一种嵌入捆绑操作的分层启发式方法，用于计算多个互不重叠、避障的欧几里得斯坦纳树，该方法对建模受限二维域中多智能体的去中心化与多点协同具有重要意义。通过在任意障碍物配置（含凸与非凸几何形状）下的计算实验，验证了该方法在平面中生成多组避障斯坦纳树的可行性与优异性能。结果揭示了新型避障斯坦纳树运算符的设计机制。
原文摘要 · Abstract (English)
Euclidean Steiner trees are relevant to model minimal networks in real-world applications ubiquitously. In this paper, we study the feasibility of a hierarchical approach embedded with bundling operations to compute multiple and mutually disjoint Euclidean Steiner trees that avoid clutter and overlapping with obstacles in the plane, which is significant to model the decentralized and the multipoint coordination of agents in constrained 2D domains. Our computational experiments using arbitrary obstacle configuration with convex and non-convex geometries show the feasibility and the attractive performance when computing multiple obstacle-avoiding Steiner trees in the plane. Our results offer the mechanisms to elucidate new operators for obstacle-avoiding Steiner trees.
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