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针对农业果树采摘手段原始和机械落后状况,首次提出面向虚拟农业智能移动机器人采摘行为的知识建模。首先研究虚拟环境(VE)下机器人采摘行为,提出了层次结构和行为的知识建模方法,对VE中的机器人结构和行为进行知识分类和表达。其次,建立了关联知识库和知识模型。然后,提出基于粗糙集的行为知识分类处理,把农业智能移动机器人的作业行为分为三类行为,通过分类对冗余知识进行属性约简。最后,通过知识建模,实现了VE下机器人的行为推理和仿真。
According to the primitive and mechanical backwardness of agricultural fruit picking tools, the knowledge modeling for the picking behavior of virtual agriculture intelligent mobile robots is proposed for the first time. Firstly, the robot picking behavior under virtual environment (VE) is studied. A knowledge modeling method of hierarchy and behavior is put forward to classify and express the knowledge of robot structure and behavior in VE. Second, the establishment of the associated knowledge base and knowledge model. Then, the classification of behavioral knowledge based on rough set is proposed. The operational behaviors of agricultural intelligent mobile robots are divided into three types of behaviors, and attribute reduction of redundant knowledge is carried out by classification. Finally, through knowledge modeling, the behavior reasoning and simulation of robot under VE is realized.