Extracting behavior knowledge and modeling based on virtual agricultural mobile robot

  • Authors:

  • Xiangjun Zou;Jun Lu;Lufeng Luo;Xiwen Luo;Yanqiong Zhou

  • Affiliations:

  • The College of Engineering, South China Agriculture University, Guangzhou;The College of Engineering, South China Agriculture University, Guangzhou;The College of Engineering, South China Agriculture University, Guangzhou;The College of Engineering, South China Agriculture University, Guangzhou;Nanhua University, Hengyang, Hunan, China

  • Venue:
  • ICAT'06 Proceedings of the 16th international conference on Advances in Artificial Reality and Tele-Existence
  • Year:
  • 2006

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Abstract

Aiming at complexity, unknown and uncertainty of picking object of agricultural intelligence mobile robot, extracting behavior knowledge and modeling based on the robot was put forward to help them obtain information effectively during operation, thereby to make decision for their behaviors. Firstly, behavior was studied based on picking behavior of the robot in virtual environment. Propose a behavior and method of extracting knowledge in virtual environment those are based on the association rules and, classify and express the entities such as robots, fruit trees and litchi, etc. Secondly, knowledge bases and models were built for reasoning. Thirdly, put forward for the first time to behavior knowledge classifies based on rough sets systematically, and classify the behaviors into obstacle-avoidance, picking, reasoning and fusion behavior to reduce redundant knowledge. Finally, an example for reasoning and simulation of the behavior was given. It realized picking behavior by message and route mechanism.