Performance evaluation of autonomous driving control algorithm for a crawler-type agricultural vehicle based on low-cost multi-sensor fusion positioning

Joong Hee Han, Chi Ho Park, Jay Hyoun Kwon, Jisun Lee, Tae Soo Kim, Young Yoon Jang

Research output: Contribution to journalArticlepeer-review

29 Scopus citations

Abstract

The agriculture sector is currently facing the problems of aging and decreasing skilled labor, meaning that the future direction of agriculture will be a transition to automation and mechanization that can maximize efficiency and decrease costs. Moreover, interest in the development of autonomous agricultural vehicles is increasing due to advances in sensor technology and information and communication technology (ICT). Therefore, an autonomous driving control algorithm using a low-cost global navigation satellite system (GNSS)-real-time kinematic (RTK) module and a low-cost motion sensor module was developed to commercialize an autonomous driving system for a crawler-type agricultural vehicle. Moreover, an autonomous driving control algorithm, including the GNSS-RTK/motion sensor integration algorithm and the path-tracking control algorithm, was proposed. Then, the performance of the proposed algorithm was evaluated based on three trajectories. The Root Mean Square Errors (RMSEs) of the path-following of each trajectory are calculated to be 9, 7, and 7 cm, respectively, and the maximum error is smaller than 30 cm. Thus, it is expected that the proposed algorithm could be used to conduct autonomous driving with about a 10 cm-level of accuracy.

Original languageEnglish
Article number4667
JournalApplied Sciences (Switzerland)
Volume10
Issue number13
DOIs
StatePublished - 1 Jul 2020

Keywords

  • Agricultural vehicle
  • Autonomous driving
  • Crawler type
  • GNSS-RTK
  • Motion sensor
  • Sensor fusion

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