[1]黄心汉,李 鹏,王 敏.广义证据推理融合结构[J].智能系统学报,2010,5(6):487-491.
HUANG Xin-han,LI Peng,WANG Min.General evidence reasoning fusion structure[J].CAAI Transactions on Intelligent Systems,2010,5(6):487-491.
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HUANG Xin-han,LI Peng,WANG Min.General evidence reasoning fusion structure[J].CAAI Transactions on Intelligent Systems,2010,5(6):487-491.
广义证据推理融合结构
《智能系统学报》[ISSN 1673-4785/CN 23-1538/TP] 卷:
5
期数:
2010年第6期
页码:
487-491
栏目:
学术论文—人工智能基础
出版日期:
2010-12-25
- Title:
- General evidence reasoning fusion structure
- 文章编号:
- 1673-4785(2010)06-0487-05
- Keywords:
- evidence reasoning; fusion frame; map building; information fusion
- 分类号:
- TP242.6
- 文献标志码:
- A
- 摘要:
- 针对DempsterShafer理论（DST）及DezertSmarandache理论（DSmT）难以处理不确定信息的问题，定义了辨识框架中的不确定因子，提出了2种自适应通用分配法则（AUPR）.并提出了证据理论的广义融合框架，并在此基础上构建了广义证据推理机.以Pioneer 2DXe机器人为实验平台，绘制了实验场景的信度分布图.实验结果验证了所提方法的有效性和实用性，为构建统一的信息融合框架提供了有力的依据.
- Abstract:
- In order to solve the problem of the DempsterShafer theory (DST) and DezertSmarandache theory (DSmT) both being unable to deal with uncertain information, the uncertainty mass in the frame was defined and two kinds of adaptive universal proportional redistribution rules (AUPR) were proposed. Next, a general evidence reasoning fusion structure was proposed based on the general evidence with which the reasoning machine was built. Lastly, the pioneer 2DXe mobile robot was used to build the belief distribution maps of various environments. The experimental results verify the validity and the practicality of the proposed methods. They also supply powerful theoretical evidence for constructing a uniform information fusion frame.
- 参考文献/References:
-
［1］SHAFER G. A mathematical theory of evidence［M］. Princeton, USA: Princeton University Press, 1976： 1100.
［2］DEZERT J. Foundations for a new theory of plausible and paradoxical reasoning［J］. Information and Security, 2002, 9: 1357.
［3］SMARANDACHE F, DEZERT J. Advances and applications of DSmT for information fusion［M］. Rehoboth, USA: American Research Press, 2004: 331.
［4］SMARANDACHE F, DEZERT J. Advances and applications of DSmT for information fusion［M］. Rehoboth, USA: American Research Press, 2006: 4749.
［5］SMARANDACHE F, DEZERT J. Advances and applications of DSmT for information fusion［M］. Rehoboth, USA: American Research Press, 2009： 137160.
［6］HUANG Xinhan, LI Peng, WANG Min. Evidence reasoning machine based on DSmT for mobile robot mapping in unknown dynamic environment［C］//2009 IEEE International Conference on Robotics and Biomimetics. Guilin, China: 2009： 753758.
［7］李鹏, 黄心汉, 王敏. 基于混合DSm模型的移动机器人动态环境地图构建［J］. 机器人, 2009, 31(1): 4046, 52.
?LI Peng, HUANG Xinhan, WANG Min. HybridDSmmodelbased mobile robot map building in dynamic environment［J］. Robotics, 2009, 31(1): 4046, 52.
- 相似文献/References:
-
[1]陈楠楠,巩晓婷,傅仰耿.基于改进规则激活率的扩展置信规则库推理方法[J].智能系统学报,2019,14(6):1179.[doi:10.11992/tis.201906046]
CHEN Nannan,GONG Xiaoting,FU Yanggeng.Extended belief rule-based reasoning method based on an improved rule activation rate[J].CAAI Transactions on Intelligent Systems,2019,14():1179.[doi:10.11992/tis.201906046]
备注/Memo
收稿日期：2010-04-21.
基金项目：国家自然科学基金资助项目（60675028）.
通信作者：黄心汉.E-mail:xhhuang@mail.hust.edu.cn.
作者简介：
黄心汉，男，1946年生，教授，博士生导师.主要研究方向为智能控制、智能机器人、多传感器集成与信息融合等.曾任国家“863”计划智能机器人主题控制专题专家组成员.现任中国人工智能学会常务理事、智能机器人专业委员会主任等职.发表学术论文300余篇.
李鹏，男，1981年生，博士研究生.主要研究方向为信息融合、机器人地图创建与定位、多机器人系统.发表学术论文10余篇.
王 敏，女，1954年生，教授.主要研究方向为图像处理与模式识别技术、机器人视觉与传感技术、智能控制与神经元网络原理及应用等.现任中国人工智能学会理事、智能机器人专业委员会秘书长等职.发表学术论文80余篇，出版教材3部.
更新日期/Last Update:
2011-03-03