Proceedings of 1994 IEEE International Conference on MFI '94. Multisensor Fusion and Integration for Intelligent Systems最新文献_第7页

Multi-sensor fault detection and diagnosis using combined qualitative and quantitative techniques 采用定性与定量相结合的多传感器故障检测与诊断方法

Proceedings of 1994 IEEE International Conference on MFI '94. Multisensor Fusion and Integration for Intelligent Systems Pub Date : 1994-10-02 DOI: 10.1109/MFI.1994.398474

Yang Gao, H. Durrant-Whyte

引用次数: 9

An auto calibration scheme for sensor fusion 一种传感器融合的自动校准方案

Proceedings of 1994 IEEE International Conference on MFI '94. Multisensor Fusion and Integration for Intelligent Systems Pub Date : 1994-10-02 DOI: 10.1109/MFI.1994.398464

E. C. Yeh, Chien-Sheng Wang

引用次数: 1

Multi-layered fuzzy behavior fusion for real-time control of systems with many sensors 多传感器系统实时控制的多层模糊行为融合

Proceedings of 1994 IEEE International Conference on MFI '94. Multisensor Fusion and Integration for Intelligent Systems Pub Date : 1994-10-02 DOI: 10.1109/MFI.1994.398443

S. G. Goodridge, R. Luo, M. Kay

引用次数: 37

Use of tactile sensors in enhancing the efficiency of vision-based object localization 利用触觉传感器提高基于视觉的物体定位效率

Proceedings of 1994 IEEE International Conference on MFI '94. Multisensor Fusion and Integration for Intelligent Systems Pub Date : 1994-10-02 DOI: 10.1109/MFI.1994.398446

M. Boshra, Hong Zhang

引用次数: 6

Evidence combination using fuzzy linguistic terms in a dynamic, multisensor environment 在动态、多传感器环境中使用模糊语言术语的证据组合

Proceedings of 1994 IEEE International Conference on MFI '94. Multisensor Fusion and Integration for Intelligent Systems Pub Date : 1994-10-02 DOI: 10.1109/MFI.1994.398428

B. Hussien, F. Ismael, M. Bender

{"title":"Evidence combination using fuzzy linguistic terms in a dynamic, multisensor environment","authors":"B. Hussien, F. Ismael, M. Bender","doi":"10.1109/MFI.1994.398428","DOIUrl":"https://doi.org/10.1109/MFI.1994.398428","url":null,"abstract":"There have been few procedures that effectively manage certainty for real-time multi-sensor environments such as battlefield decision making. In these environments inferences are rarely certain due to: unreliable data, inappropriate inference rules, and indeterminate temporal nature of data. Thus, there is a vital need for an effective certainty management scheme for these real-world applications. This paper presents extensions to our earlier paper (1989) and presents a formalism for computing membership functions as a mechanism for combining evidence. It proposes a \"unified\" methodology that combines certainties associated with evidence and rules for a given proposition, and systematically propagates these certainties down the (rule-based) decision tree. The methodology takes into account the relative importance of the propositions as well as the rules. The proposed methodology supports both numeric certainty values and linguistic variables that model human cognition. In addition, the methodology supports \"confirmation\" and \"disconfirmation\" constructs that are very useful for knowledge engineering.<<ETX>>","PeriodicalId":133630,"journal":{"name":"Proceedings of 1994 IEEE International Conference on MFI '94. Multisensor Fusion and Integration for Intelligent Systems","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1994-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133440709","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 4

Potential-based modeling of two dimensional workspace using several source distributions 使用多个源分布的二维工作空间的基于电位的建模

Proceedings of 1994 IEEE International Conference on MFI '94. Multisensor Fusion and Integration for Intelligent Systems Pub Date : 1994-10-02 DOI: 10.1109/MFI.1994.398468

Jen-Hui Chuang

引用次数: 1

Multi-sensory fusion and model-based recognition of complex objects 多感官融合与基于模型的复杂物体识别

Proceedings of 1994 IEEE International Conference on MFI '94. Multisensor Fusion and Integration for Intelligent Systems Pub Date : 1994-10-02 DOI: 10.1109/MFI.1994.398434

M. Devy, R. Boumaza

{"title":"Multi-sensory fusion and model-based recognition of complex objects","authors":"M. Devy, R. Boumaza","doi":"10.1109/MFI.1994.398434","DOIUrl":"https://doi.org/10.1109/MFI.1994.398434","url":null,"abstract":"Perception with complementary sensors like a color camera and a laser range finder, make easier the recognition of objects in a 3D scene. This paper copes with the recognition of non-polyhedral objects, described each one by a REV graph and an aspect table, required to afford reasoning about visibility. The authors focus on the relations between segmentation and recognition strategies. A set of segmentation operators, executed by logical sensors, can be requested with respect to the state of the recognition task, in order to extract the more suitable set of features from the sensory data; if needed, the fusion of perceptual data can provide the more accurate estimates of the perceived geometric features. The control module of the recognition task, follows a classical \"hypothesize and test\" paradigm; this paper concerns only the hypothesis generation and verification, after one acquisition. Recognition strategies could be compiled off line, according to the object and the sensor models. The authors show how such strategies allow one to limit complexity of the segmentation and recognition processes; experimental results on real perceptual data, validate this method.<<ETX>>","PeriodicalId":133630,"journal":{"name":"Proceedings of 1994 IEEE International Conference on MFI '94. Multisensor Fusion and Integration for Intelligent Systems","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1994-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128851462","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 7

The use of fuzzy neural networks for feature/sensor selection 使用模糊神经网络进行特征/传感器选择

Proceedings of 1994 IEEE International Conference on MFI '94. Multisensor Fusion and Integration for Intelligent Systems Pub Date : 1994-10-02 DOI: 10.1109/MFI.1994.398398

M. E. Ulug

引用次数: 4

Posture estimation of mobile robots: observers-sensors 移动机器人姿态估计:观测器-传感器

Proceedings of 1994 IEEE International Conference on MFI '94. Multisensor Fusion and Integration for Intelligent Systems Pub Date : 1994-10-02 DOI: 10.1109/MFI.1994.398391

H. Medromi, J. Tigli, M. Thomas

引用次数: 5

A priority-based parallel architecture for sensor fusion 基于优先级的传感器融合并行架构

Proceedings of 1994 IEEE International Conference on MFI '94. Multisensor Fusion and Integration for Intelligent Systems Pub Date : 1994-10-02 DOI: 10.1109/MFI.1994.398467

K. Nishida, K. Toda, E. Takahashi, Y. Yamaguchi

引用次数: 4