摘要翻译：
近15年前，Schlieder提出了一组定向直线段（偶极子）之间的定性空间关系。这项工作受到了定性空间推理界的极大兴趣。然而，在这些关系的基础上建立一个健全的约束演算是困难的。本文给出了偶极子约束演算的一个新的研究结果，它用代数方法导出了偶极子演算的关系合成和其他性质的合理结果。我们的结果是基于偶极子关系的一个压缩语义。与通常使用的点不同，偶极子是扩展的，并且有一个固有的方向。这两个特征都是自然物体的重要性质。这允许空间代理的原型推理任务的直接表示。作为一个例子，我们展示了如何从街道网络中的局部观测中生成调查知识。这个例子说明了偶极子演算的快速约束推理能力。我们将我们的结果集成到两个公开的推理工具中。
---
英文标题：
《Oriented Straight Line Segment Algebra: Qualitative Spatial Reasoning
  about Oriented Objects》
---
作者：
Reinhard Moratz, Dominik L\"ucke, Till Mossakowski
---
最新提交年份：
2009
---
分类信息：

一级分类：Computer Science        计算机科学
二级分类：Artificial Intelligence        人工智能
分类描述：Covers all areas of AI except Vision, Robotics, Machine Learning, Multiagent Systems, and Computation and Language (Natural Language Processing), which have separate subject areas. In particular, includes Expert Systems, Theorem Proving (although this may overlap with Logic in Computer Science), Knowledge Representation, Planning, and Uncertainty in AI. Roughly includes material in ACM Subject Classes I.2.0, I.2.1, I.2.3, I.2.4, I.2.8, and I.2.11.
涵盖了人工智能的所有领域，除了视觉、机器人、机器学习、多智能体系统以及计算和语言（自然语言处理），这些领域有独立的学科领域。特别地，包括专家系统，定理证明（尽管这可能与计算机科学中的逻辑重叠），知识表示，规划，和人工智能中的不确定性。大致包括ACM学科类I.2.0、I.2.1、I.2.3、I.2.4、I.2.8和I.2.11中的材料。
--

---
英文摘要：
  Nearly 15 years ago, a set of qualitative spatial relations between oriented straight line segments (dipoles) was suggested by Schlieder. This work received substantial interest amongst the qualitative spatial reasoning community. However, it turned out to be difficult to establish a sound constraint calculus based on these relations. In this paper, we present the results of a new investigation into dipole constraint calculi which uses algebraic methods to derive sound results on the composition of relations and other properties of dipole calculi. Our results are based on a condensed semantics of the dipole relations.   In contrast to the points that are normally used, dipoles are extended and have an intrinsic direction. Both features are important properties of natural objects. This allows for a straightforward representation of prototypical reasoning tasks for spatial agents. As an example, we show how to generate survey knowledge from local observations in a street network. The example illustrates the fast constraint-based reasoning capabilities of the dipole calculus. We integrate our results into two reasoning tools which are publicly available.
---
PDF链接：
https://arxiv.org/pdf/0912.5533