Research on the calibration method for the heading errors of mobile robot based on evolutionary neural network prediction

  • Authors:

  • Jinxia Yu;Zixing Cai;Xiaobing Zou;Zhuohua Duan

  • Affiliations:

  • College of Information Science and Engineering, Central South University, Changsha, Hunan, China;College of Information Science and Engineering, Central South University, Changsha, Hunan, China;College of Information Science and Engineering, Central South University, Changsha, Hunan, China;College of Information Science and Engineering, Central South University, Changsha, Hunan, China

  • Venue:
  • ISNN'05 Proceedings of the Second international conference on Advances in Neural Networks - Volume Part III
  • Year:
  • 2005

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Abstract

Fiber optic gyros (FOG) is the important sensor for measuring the heading of mobile robot. Combined with measured data of E-Core RD1100 interferometric FOG made by American KVH company, the paper analyses the common calibration for the heading errors of mobile robot caused by the drift of FOG, and uses the method of evolutionary neural networks prediction to compensate it. By the experiments of mobile robot prototype, the paper also proves this method can reduce the error influence of FOG on the heading of mobile robot and enhance the localization precision of mobile robot navigation.