A sensor fusion framework for online sensor and algorithm selection

Ofir Cohen; Yael Edan

doi:10.1016/j.robot.2007.12.002

A sensor fusion framework for online sensor and algorithm selection

Ofir Cohen, Yael Edan

Department of Industrial Engineering and Management

Research output: Contribution to journal › Article › peer-review

12 Scopus citations

Abstract

This paper presents a sensor fusion framework for selecting online the most reliable logical sensors and the most suitable algorithm for fusing sensor data in a robot platform. The framework is rule-based, employing the concept of using the simplest sensor fusion algorithm with the most reliable sensors. The framework is realized by implementing measures that were developed to quantify online sensor performance. Statistical, histogram, time series and graphical analyses demonstrate the advantages of this new framework.

Original language	English
Pages (from-to)	762-776
Number of pages	15
Journal	Robotics and Autonomous Systems
Volume	56
Issue number	9
DOIs	https://doi.org/10.1016/j.robot.2007.12.002
State	Published - 30 Sep 2008

Keywords

Algorithm selection
Mobile robots
Performance measures
Sensor fusion

Access to Document

10.1016/j.robot.2007.12.002

Cite this

@article{2e82a22791b44208bf7c8b9a9e7d3c39,

title = "A sensor fusion framework for online sensor and algorithm selection",

abstract = "This paper presents a sensor fusion framework for selecting online the most reliable logical sensors and the most suitable algorithm for fusing sensor data in a robot platform. The framework is rule-based, employing the concept of using the simplest sensor fusion algorithm with the most reliable sensors. The framework is realized by implementing measures that were developed to quantify online sensor performance. Statistical, histogram, time series and graphical analyses demonstrate the advantages of this new framework.",

keywords = "Algorithm selection, Mobile robots, Performance measures, Sensor fusion",

author = "Ofir Cohen and Yael Edan",

year = "2008",

month = sep,

day = "30",

doi = "10.1016/j.robot.2007.12.002",

language = "English",

volume = "56",

pages = "762--776",

journal = "Robotics and Autonomous Systems",

issn = "0921-8890",

publisher = "Elsevier",

number = "9",

}

TY - JOUR

T1 - A sensor fusion framework for online sensor and algorithm selection

AU - Cohen, Ofir

AU - Edan, Yael

PY - 2008/9/30

Y1 - 2008/9/30

N2 - This paper presents a sensor fusion framework for selecting online the most reliable logical sensors and the most suitable algorithm for fusing sensor data in a robot platform. The framework is rule-based, employing the concept of using the simplest sensor fusion algorithm with the most reliable sensors. The framework is realized by implementing measures that were developed to quantify online sensor performance. Statistical, histogram, time series and graphical analyses demonstrate the advantages of this new framework.

AB - This paper presents a sensor fusion framework for selecting online the most reliable logical sensors and the most suitable algorithm for fusing sensor data in a robot platform. The framework is rule-based, employing the concept of using the simplest sensor fusion algorithm with the most reliable sensors. The framework is realized by implementing measures that were developed to quantify online sensor performance. Statistical, histogram, time series and graphical analyses demonstrate the advantages of this new framework.

KW - Algorithm selection

KW - Mobile robots

KW - Performance measures

KW - Sensor fusion

UR - http://www.scopus.com/inward/record.url?scp=49649122075&partnerID=8YFLogxK

U2 - 10.1016/j.robot.2007.12.002

DO - 10.1016/j.robot.2007.12.002

M3 - Article

AN - SCOPUS:49649122075

VL - 56

SP - 762

EP - 776

JO - Robotics and Autonomous Systems

JF - Robotics and Autonomous Systems

SN - 0921-8890

IS - 9

ER -

A sensor fusion framework for online sensor and algorithm selection

Abstract

Keywords

Access to Document

Other files and links

Fingerprint

Cite this