An EKF SLAM algorithm for mobile robot with sensor bias estimation

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20 Scopus citations

Abstract

This paper presents an improved EKF method applied into mobile robot SLAM problem, which has taken the sensor bias problem into consideration. Mobile robot Pioneer 3-AT is taken as the model in this paper to study on the theoretical derivation and the experimental verification. The kinematic model of Pioneer 3-AT mobile robot is presented at first. Then the improved EKF method considering the bias estimation and compensation problem is proposed to enhance the position estimation accuracy. In the end, simulation experiments are presented to verify the effectiveness of the proposed method. The results show that the method is always effective on ensuring the estimation accuracy even though with unknown bias.

Original languageEnglish
Title of host publicationProceedings - 2017 32nd Youth Academic Annual Conference of Chinese Association of Automation, YAC 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages281-285
Number of pages5
ISBN (Electronic)9781538629017
DOIs
StatePublished - 30 Jun 2017
Externally publishedYes
Event32nd Youth Academic Annual Conference of Chinese Association of Automation, YAC 2017 - Hefei, China
Duration: 19 May 201721 May 2017

Publication series

NameProceedings - 2017 32nd Youth Academic Annual Conference of Chinese Association of Automation, YAC 2017

Conference

Conference32nd Youth Academic Annual Conference of Chinese Association of Automation, YAC 2017
Country/TerritoryChina
CityHefei
Period19/05/1721/05/17

Keywords

  • Extended Kalman Filtering (EKF)
  • Mobile robot
  • Simultaneous localization and mapping (SLAM)

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