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    一种基于OPRA\-4方向关系推理定性距离变化的方法

    A Reasoning Method for Qualitative Distance Change Based on OPRA\-4 Direction Relations

    • 摘要: 空间信息包含方向、拓扑、形状、距离等多种关系.定性空间关系表示与推理是人工智能的重要研究子域,在空间信息系统、机器人导航、自然语言理解、智能交通等领域有着广泛的应用.以往研究多面向静态空间对象,侧重单一空间关系,对不同空间关系间的约束研究不够深入,难以基于一种空间关系对另一种空间关系的演变做出有效推理.针对移动空间对象之间定性方向关系与定性距离变化的结合推理问题,利用射线与圆之间位置关系的组合来描述2个空间对象之间的相对移动方向;分别研究并证明该位置关系的组合对定性距离变化的约束作用、该位置关系的组合与粒度为4的有向点方向代数(oriented point algebra with granularity of 4, OPRA\-4)间的对应关系,进而建立起OPRA\-4方向关系与定性距离变化之间的内在联系;提出一种基于基本OPRA\-4方向关系推理定性距离变化的方法,并结合交通领域中的连续k近邻查询实例说明该方法的正确性和有效性.

       

      Abstract: Spatial information includes many relations such as direction, topology, shape, distance, etc. Qualitative spatial representation and reasoning has become an important subfield of artificial intelligence, and has gained increasing popularity in recent years with applications in spatial information systems, robot navigation, natural language understanding, intelligent transportation system and so on. Previous studies are mostly oriented to static spatial objects, and focus on a single kind of spatial relation. The research on constraints between different kinds of spatial relations is insufficient, and it is difficult to make use of one kind of spatial relation to reason about the evolution of another spatial relation effectively. In this study, we focus on the qualitative direction relations and distance changes of moving spatial objects. Firstly, the relative moving direction between two spatial objects is described by a combination of the position relations between the corresponding ray and the circle. Secondly, the restrictions of the combinations on the qualitative distance changes, and the corresponding relationship between the combinations and oriented point algebra with granularity of 4 (OPRA\-4) are studied respectively. And then the connection between the OPRA\-4 direction relations and the qualitative distance changes is established. Finally, an approach to reasoning about the qualitative distance changes with basic OPRA\-4 direction relations is presented. The correctness and effectiveness of the approach are illustrated by an example of continuous k nearest neighbor queries of moving objects in traffic field.

       

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