Bioinspired in-grid navigation and positioning based on an artificially established magnetic gradient

Xiaokang Qi, Lei Chen, Kang An, Jun Wang, Bin Zhang, Kuiwen Xu, Dexin Ye, Changzhi Li, Lixin Ran

Research output: Contribution to journalArticle

Abstract

In the past years, significant progresses have been achieved in signpost-based indoor navigation and positioning systems. In this paper, inspired by recent bionic researches on long-distance animal geomagnetic navigation, we propose an autonomous local navigation and positioning system, based on an artificially established magnetic gradient for in-grid or desktop applications. Without using any magnetic-field strength information, the proposed navigation and positioning can be accomplished by matching a spatial angle included by the direction of the vector magnetic field and a direction defined in the navigation plane using an algorithm derived based on the Kalman filter. Simulations and experiments verified the effectiveness of the proposed approach. This method can be used to improve the positioning precision of signpost-based systems. It can also be used in new applications of autonomous in-grid or desktop navigation and positioning for automatic robot arms.

Original languageEnglish
Article number8443112
Pages (from-to)10583-10589
Number of pages7
JournalIEEE Transactions on Vehicular Technology
Volume67
Issue number11
DOIs
StatePublished - Nov 2018

Keywords

  • In-grid magnetic positioning
  • Kalman filter
  • animal navigation
  • indoor positioning
  • magnetic gradient

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