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FAN Bowen, XUE Jinlin. Velocity control strategy based on a cloud model for unmanned agricultural vehicle during obstacle crossing[J]. Journal of South China Agricultural University, 2018, 39(4): 114-119. DOI: 10.7671/j.issn.1001-411X.2018.04.018
Citation: FAN Bowen, XUE Jinlin. Velocity control strategy based on a cloud model for unmanned agricultural vehicle during obstacle crossing[J]. Journal of South China Agricultural University, 2018, 39(4): 114-119. DOI: 10.7671/j.issn.1001-411X.2018.04.018

Velocity control strategy based on a cloud model for unmanned agricultural vehicle during obstacle crossing

More Information
  • Received Date: October 18, 2017
  • Available Online: May 17, 2023
  • Objective 

    To improve the intelligence and safety of remote-operated agricultural vehicles.

    Method 

    A new method for unmanned agricultural vehicles during obstacle crossing was proposed. The collision prediction model of unmanned vehicles in dynamic environment was established, and the real-time collision location was determined. According to the cloud inference principle based on both experience of experts and agricultural operation environment, velocity control strategy was established to realize velocity control.

    Result 

    The algorithm took 0.170 1 s on average to make a prediction, the velocity control results of unmanned vehicles excluded the impact of non-threatening obstacles and accorded with the velocity cloud inference principle.

    Conclusion 

    The established algorithm is able to realize real-time collision prediction, possesses anti-disturbance ability, and satisfies real-time requirement.

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