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Soil type identification for autonomous excavation based on dissipation energy

机译:基于耗散能量的自主开挖土壤类型识别

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Knowledge of soil properties and identifying worked soil type are critical for optimized control strategies of an autonomous excavator. The current paper presents an online soil type identification based on real-time measuring of energy components for horizontal dragging tasks. The online energy measurement, calculated by integration of the force acting on an object along a displacement, makes the resulting data robust to noise. Analysis of the energy measurement reveals that the correlation between potential-dissipation energy and displacement has unique characteristics for any given soil, independently of the amount of applied force. This leads to the creation of a new soil 'energy map' with respect to various soil types. A mathematical model has been developed for each soil's 'energy map'. An identification algorithm has been developed to utilize these prior mathematical models for cross-referencing with online total energy of the currently worked soil to identify soil type online. The overall approach has been validated experimentally on a laboratory test-rig using mulch, gravel, sand, and clay soils.
机译:对于自动挖掘机的优化控制策略,了解土壤特性和确定工作土壤类型至关重要。当前论文提出了一种基于实时测量水平拖动任务能量分量的在线土壤类型识别方法。通过对沿位移作用在对象上的力进行积分来计算在线能量测量值,从而使所得数据对噪声具有鲁棒性。能量测量的分析表明,对于任何给定的土壤,势能耗散能量与位移之间的相关性具有独特的特性,而与施加的力无关。这导致针对各种土壤类型创建新的土壤“能量图”。已经为每种土壤的“能量图”开发了数学模型。已经开发出一种识别算法,以利用这些现有的数学模型与当前工作土壤的在线总能量进行交叉参考,从而在线识别土壤类型。整体方法已在覆盖土,砾石,沙子和粘土的实验室试验台上进行了实验验证。

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