A sensor fusion framework for online sensor and algorithm selection

Ofir Cohen, Yael Edan

Research output: Contribution to journalArticlepeer-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 languageEnglish
Pages (from-to)762-776
Number of pages15
JournalRobotics and Autonomous Systems
Volume56
Issue number9
DOIs
StatePublished - 30 Sep 2008

Keywords

  • Algorithm selection
  • Mobile robots
  • Performance measures
  • Sensor fusion

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