Adaptive weighted average sensor fusion algorithms for mobile robots

Keren Kapach, Yael Edan

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

This paper presents a new set of sensor fusion algorithms for mapping the environment of mobile robots using grid maps. The algorithms use the adaptive weighted average method and consider as weights the number of times each cell was sampled by the sensor. Analysis in an indoor mobile robot experiment indicated superior performance of one of the new algorithms when compared to a previously developed adaptive fuzzy logic algorithm.

Original languageEnglish
Title of host publicationMCCSIS 2007 - IADIS Multi Conference on Computer Science and Information Systems - Proceedings of Intelligent Systems and Agents 2007, Interfaces and Human Computer Interaction 2007, Computer Graphics and Visualization 2007
EditorsAntonio Palma dos Reis, Katherine Blashki, Yingcai Xiao
PublisherIADIS Press
Pages43-50
Number of pages8
ISBN (Electronic)9789728924393
StatePublished - 1 Jan 2007
Event2007 IADIS International Conference on Intelligent Systems and Agents, ISA 2007, part of the 1st IADIS Multi Conference on Computer Science and Information Systems, MCCSIS 2007 - Lisbon, Portugal
Duration: 3 Jul 20078 Jul 2007

Publication series

NameMCCSIS 2007 - IADIS Multi Conference on Computer Science and Information Systems - Proceedings of Intelligent Systems and Agents 2007, Interfaces and Human Computer Interaction 2007, Computer Graphics and Visualization 2007
VolumePart 1

Conference

Conference2007 IADIS International Conference on Intelligent Systems and Agents, ISA 2007, part of the 1st IADIS Multi Conference on Computer Science and Information Systems, MCCSIS 2007
Country/TerritoryPortugal
CityLisbon
Period3/07/078/07/07

Keywords

  • Algorithms
  • Autonomous mobile robots
  • Robotics
  • Sensor fusion

ASJC Scopus subject areas

  • Computer Science (all)

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