虚拟农业移动机器人采摘行为的知识建模

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。

Knowledge modeling of virtual agricultural mobile robot's picking behavior

Making a analysis of the picking method in less efficiency and machine behind the times in agricultural fruits picking in our country at the present time, picking behavior knowledge modeling based on the robot was put forward to help them obtain information effectively during operation, thereby to make decision for their behavior. Firstly, behavior was studied based on picking behavior of the robot in virtual environment(VE). Propose the knowledge modeling method of layer structure and behavior, classify and express the entities such as robots, fruit trees and litchi, etc. Secondly, build association repository and knowledge models. Thirdly, put forward for the first time to behavior information classifies based on rough sets systematically, and classifies the robot's behavior into three main types to reduce redundant knowledge. Finally, achieve reasoning and simulation of picking behavior in VE.