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Orchard traveling UGV using particle filter based localization and inverse optimal control

机译:果园旅行UGV基于粒子过滤器的定位和逆最佳控制

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The authors previously proposed an Unmanned Ground Vehicle (UGV) in an orchard as a base platform for autonomous robot systems for performing tasks such as monitoring, pesticide spraying, and harvesting. To control a UGV in a semi-natural environment, accurate self-localization and a control law that is robust under large disturbances from rough terrain are the first priorities. In this paper, a self-localization algorithm consisting of a 2D laser range finder and the particle filter is proposed. A robust nonlinear control law and a path regeneration algorithm that the authors proposed for underactuated mobile robots are combined with the localization method and applied to a drive-by-wire experimental vehicle. Excellent experimental results were obtained for traveling through a real orchard. The standard deviation of the control error in the lateral direction was less than 15cm.
机译:此前提出了一个在果园中的无人机地面车辆(UGV)作为自主机器人系统的基础平台,用于执行监测,农药喷涂和收获的任务。在半自然环境中控制UGV,准确的自我定位和对粗糙地形的大扰动的控制法是第一个优先事项。本文提出了一种由2D激光测距仪和颗粒滤波器组成的自定位算法。坚固的非线性控制定律和路径再生算法,即欠扰动的移动机器人提出的作者与定位方法相结合并应用于逐线实验载体。获得了优秀的实验结果,用于通过真正的果园旅行。控制误差在横向方向上的标准偏差小于15cm。

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