吉林大学学报(工学版) ›› 2015, Vol. 45 ›› Issue (5): 1535-1540.doi: 10.13229/j.cnki.jdxbgxb201505023

• • 上一篇    下一篇

基于OPRAm的三维相对方位关系模型

欧阳继红1, 祝东红1, 2, 富倩2, 杨帅2, 陈思2   

  1. 1.吉林大学 计算机科学与技术学院,长春 130012;
    2.吉林大学 符号计算与知识工程教育部重点实验室,长春 130012
  • 收稿日期:2013-07-02 出版日期:2015-09-01 发布日期:2015-09-01
  • 作者简介:欧阳继红(1964-),女,教授,博士生导师.研究方向:空间推理,不确定性推理,GIS应用.E-mail:ouyj@jlu.edu.cn
  • 基金资助:
    国家自然科学基金项目(61170092,61133011,61272208,61103091,61202308)

Model for three-directional relative directions based on OPRAm

OUYANG Ji-hong1, ZHU Dong-hong1, 2, FU Qian2, YANG Shuai2, CHEN Si2   

  1. 1.College of Computer Science and Technology,Jilin University,Changchun 130012, China;
    2.Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education, Jilin University, Changchun 130012,China
  • Received:2013-07-02 Online:2015-09-01 Published:2015-09-01

摘要: OPRAm是研究二维相对方位关系的经典模型之一,但解决实际问题通常需要考虑多维空间中的方位关系,为了表达三维空间中点对象间相对方位关系,将xoy平面相对方位和z轴相对方位相结合;通过定义与之相对应的能表达相对方位信息的两个相对角得到3DOPRAm模型,并给出其在多粒度下的形式化定义及逆关系。给出了3DOPRAm模型的概念邻域。最后用其基于动作的邻域关系描述汽车导航问题。结果表明,本文提出的模型能够细致、合理地表达三维空间中点对象间的相对方位关系,在实际中有广泛的应用前景。

关键词: 人工智能, 空间推理, 相对方位关系, OPRAm, 3DOPRAm

Abstract: OPRAm is the classical model in the study of two-dimensional direction relationship. However, to solve practical problems, the multi-directional space relationship should be considered. In order to express the relative direction in three-dimensional space, the relative direction of the xoy plane is combined with the relative direction of the z-axis. A three-dimensional relative direction model, 3DOPRAm, is proposed by extending the model OPRAm for two-dimensional direction relationship, and two new relative angles are defined. Moreover, the formal definition of 3DOPRAm multi-granularity, its reverse relationship and the conceptual neighborhood of 3DOPRAm are given. Finally, the conceptual neighborhood based on the action of 3DOPRAm model is applied to describe the car navigation problems. Results show that, compared with existing two-dimensional model, the proposed model is more expressive and can describe more relative directions in three-dimensional space, which has great potential for practical applications.

Key words: artificial intelligence, spatial reasoning, relative direction, OPRAm, 3DOPRAm

中图分类号: 

  • TP18
[1] Cohn A G. Qualiative spatial representation and reasoning techniques[J]. LNCS, 1997, 1303:1-30.
[2] 王生生, 王兆丹, 刘大有, 等. 有向线对象细节拓扑关系模型[J]. 吉林大学学报:工学版,2009,39(5): 1292-1296. Wang Sheng-sheng, Wang Zhao-dan, Liu Da-you, et al. Detailed topological relation model of directed line objects[J]. Journal of Jilin University(Engineering and Technology Edition), 2009,39(5): 1292-1296.
[3] Moratz R. Qualiative spatial reasoning about oriented points[R]. SFB/TR8 Spatial Cognition, 2004.
[4] Dylla F, Wallgrün J O. Qualitative spatial reasoning with conceptual neighborhoods for agent control[J]. Journal of Intelligent and Robotic Systems, 2007, 48(1): 55-78.
[5] Mossakowski T, Moratz R. Qualitative reasoning about relative direction of oriented points[J]. Artificial Intelligence, 2012, 180-181(2): 34-45.
[6] Chen J, Liu D, Jia H, et al. Cardinal Direction Relations in 3D Space[M]. Berlin Heidelber:Springer, 2007:623-629.
[7] Pacheco J, Escrig M T, Toledo F. Integrating 3D orientation models[C]∥5th Catalonian Conference on Artificial Intelligence, Lecture Notes in Artificial Intelligence, Springer Berlin Heidelberg,2002, 2504: 88-100.
[8] Freksa C. Temporal reasoning based on semi-intervals[J]. Artificial Intelligence, 1992, 54(1-2): 199-227.
[9] 宋小华,欧阳丹彤. 一种动态定性空间关系自动规划方法[J]. 软件学报, 2012, 23(10): 2564-2571. Song Xiao-hua,Ouyang Dan-tong. Automated planning method for dealing with dynamic qualitative spatial relations[J]. Journal of Software,2012,23(10):2564-2571.
[10] Moratz R, Dylla F, Frommberger L. A relative orientation algebra with adjustable granularity[C]∥Proceedings of the Workshop on Agents in Real-time and Dynamic Environments,2005: 61-70.
[1] 董飒, 刘大有, 欧阳若川, 朱允刚, 李丽娜. 引入二阶马尔可夫假设的逻辑回归异质性网络分类方法[J]. 吉林大学学报(工学版), 2018, 48(5): 1571-1577.
[2] 顾海军, 田雅倩, 崔莹. 基于行为语言的智能交互代理[J]. 吉林大学学报(工学版), 2018, 48(5): 1578-1585.
[3] 王旭, 欧阳继红, 陈桂芬. 基于垂直维序列动态时间规整方法的图相似度度量[J]. 吉林大学学报(工学版), 2018, 48(4): 1199-1205.
[4] 张浩, 占萌苹, 郭刘香, 李誌, 刘元宁, 张春鹤, 常浩武, 王志强. 基于高通量数据的人体外源性植物miRNA跨界调控建模[J]. 吉林大学学报(工学版), 2018, 48(4): 1206-1213.
[5] 黄岚, 纪林影, 姚刚, 翟睿峰, 白天. 面向误诊提示的疾病-症状语义网构建[J]. 吉林大学学报(工学版), 2018, 48(3): 859-865.
[6] 李雄飞, 冯婷婷, 骆实, 张小利. 基于递归神经网络的自动作曲算法[J]. 吉林大学学报(工学版), 2018, 48(3): 866-873.
[7] 刘杰, 张平, 高万夫. 基于条件相关的特征选择方法[J]. 吉林大学学报(工学版), 2018, 48(3): 874-881.
[8] 王旭, 欧阳继红, 陈桂芬. 基于多重序列所有公共子序列的启发式算法度量多图的相似度[J]. 吉林大学学报(工学版), 2018, 48(2): 526-532.
[9] 杨欣, 夏斯军, 刘冬雪, 费树岷, 胡银记. 跟踪-学习-检测框架下改进加速梯度的目标跟踪[J]. 吉林大学学报(工学版), 2018, 48(2): 533-538.
[10] 刘雪娟, 袁家斌, 许娟, 段博佳. 量子k-means算法[J]. 吉林大学学报(工学版), 2018, 48(2): 539-544.
[11] 曲慧雁, 赵伟, 秦爱红. 基于优化算子的快速碰撞检测算法[J]. 吉林大学学报(工学版), 2017, 47(5): 1598-1603.
[12] 李嘉菲, 孙小玉. 基于谱分解的不确定数据聚类方法[J]. 吉林大学学报(工学版), 2017, 47(5): 1604-1611.
[13] 邵克勇, 陈丰, 王婷婷, 王季驰, 周立朋. 无平衡点分数阶混沌系统全状态自适应控制[J]. 吉林大学学报(工学版), 2017, 47(4): 1225-1230.
[14] 王生生, 王创峰, 谷方明. OPRA方向关系网络的时空推理[J]. 吉林大学学报(工学版), 2017, 47(4): 1238-1243.
[15] 马淼, 李贻斌. 基于多级图像序列和卷积神经网络的人体行为识别[J]. 吉林大学学报(工学版), 2017, 47(4): 1244-1252.
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
No Suggested Reading articles found!