Wheel slip classification method for mobile robot in sandy terrain using in-wheel sensor

Takuya Omura, Genya Ishigami

Research output: Contribution to journalArticle


This paper proposes a method that can estimate and classify the magnitude of wheel slippage for a mobile robot in sandy terrains. The proposed method exploits a sensor suite, called an in-wheel sensor, which measures the normal force and contact angle at the wheel-sand interaction boundary. An experimental test using the in-wheel sensor reveals that the maximum normal force and exit angle of the wheel explicitly vary with the magnitude of the wheel slippage. These characteristics are then fed into a machine learning algorithm, which classifies the wheel slippage into three categories: non-stuck wheel, quasi-stuck wheel, and stuck wheel. The usefulness of the proposed method for slip classification is experimentally evaluated using a four-wheel-drive test bed rover.

Original languageEnglish
Pages (from-to)902-910
Number of pages9
JournalJournal of Robotics and Mechatronics
Issue number5
Publication statusPublished - 2017 Oct 1



  • In-wheel sensor
  • Support vector machine
  • Wheel slip classification
  • Wheel-soil interaction

ASJC Scopus subject areas

  • Computer Science(all)
  • Electrical and Electronic Engineering

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