应用云模型的无人农业车辆遇障速度控制策略

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

    • 摘要:
      目的  提高遥控操作农业车辆的智能性与安全性。
      方法  提出一种新的无人农业车辆遇障后的速度控制方法。建立动态环境中无人车辆的碰撞预测模型,确定实时碰撞位置,依据专家经验与农业作业环境制定的云推理规则,建立速度控制策略,实现速度控制。
      结果  算法预测判断平均耗时0.170 1 s,无人车辆速度控制过程没有受到无威胁障碍物影响,且符合速度云推理规则。
      结论  该算法能够实现实时碰撞预测,具备抗干扰能力,满足实时性要求。

       

      Abstract:
      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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