{"title":"Sensor selection: a geometrical approach","authors":"C. Giraud-Carrier, B. Jouvencel","doi":"10.1109/IROS.1995.526271","DOIUrl":null,"url":null,"abstract":"This paper addresses the problem of sensor selection during an automatic task, for examples, a process of data fusion, a sensing task or the design of a perceptual system for a mobile robot. The authors propose an approach based on geometrical interaction between a sensor and an environment, this approach is enlarged with Gaussian approximation to take into account the measurement noise. The Bayes reasoning allows one to estimate the information given by the multi-sensor system for a given scene. Our model takes into account the number of use of each sensor. This characteristic interests us in two ways: it is possible to discard useless sensors, and it is possible to estimate the acquisition delay for a given multi-sensor system site. With this approach, we propose a quadratic criterion which is able to describe the distance between the desired information and an available information. The effectiveness of this procedure is illustrated with an example of application concerning the sensor placement problem.","PeriodicalId":124483,"journal":{"name":"Proceedings 1995 IEEE/RSJ International Conference on Intelligent Robots and Systems. Human Robot Interaction and Cooperative Robots","volume":"16 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1995-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"27","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings 1995 IEEE/RSJ International Conference on Intelligent Robots and Systems. Human Robot Interaction and Cooperative Robots","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IROS.1995.526271","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 27

Abstract

This paper addresses the problem of sensor selection during an automatic task, for examples, a process of data fusion, a sensing task or the design of a perceptual system for a mobile robot. The authors propose an approach based on geometrical interaction between a sensor and an environment, this approach is enlarged with Gaussian approximation to take into account the measurement noise. The Bayes reasoning allows one to estimate the information given by the multi-sensor system for a given scene. Our model takes into account the number of use of each sensor. This characteristic interests us in two ways: it is possible to discard useless sensors, and it is possible to estimate the acquisition delay for a given multi-sensor system site. With this approach, we propose a quadratic criterion which is able to describe the distance between the desired information and an available information. The effectiveness of this procedure is illustrated with an example of application concerning the sensor placement problem.
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传感器选择:几何方法
本文讨论了自动任务中传感器的选择问题,例如,数据融合过程,传感任务或移动机器人感知系统的设计。作者提出了一种基于传感器与环境之间几何相互作用的方法,并将该方法扩展为高斯近似以考虑测量噪声。贝叶斯推理允许人们对给定场景的多传感器系统给出的信息进行估计。我们的模型考虑了每个传感器的使用次数。这种特性在两个方面引起了我们的兴趣:有可能丢弃无用的传感器,并且有可能估计给定多传感器系统站点的采集延迟。利用这种方法,我们提出了一个二次准则,它能够描述期望信息与可用信息之间的距离。通过一个传感器放置问题的应用实例说明了该方法的有效性。
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