Orchard traveling UGV using particle filter based localization and inverse optimal control
Orchard traveling UGV using particle filter based localization and inverse optimal control
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DOI：
10.1109/sii.2010.5708297
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发表时间：
2010-12
期刊：
影响因子：
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通讯作者：
K. Kurashiki;T. Fukao;Kenji Ishiyama;Tsuyoshi Kamiya;N. Murakami
中科院分区：
文献类型：
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作者：
K. Kurashiki;T. Fukao;Kenji Ishiyama;Tsuyoshi Kamiya;N. Murakami
作者之前提出了一个果园中的无人地面车辆（UGV）作为自主机器人系统的基础平台，用于执行监测，农药喷洒和收获等任务。为了在半自然环境中控制UGV，精确的自定位和控制律是强大的大干扰下，从粗糙的地形是第一优先事项。提出了一种基于二维激光测距仪和粒子滤波的自定位算法。将本文提出的欠驱动移动的机器人鲁棒非线性控制律和路径再生算法与定位方法相结合，并应用于线控实验车。在穿越真实的果园时获得了良好的实验结果。横向控制误差的标准差小于15cm。
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.