Paper Info
Title
Extracting behavior knowledge and modeling based on virtual agricultural mobile robot
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.
Year
DOI
Venue
2006
10.1007/11941354_4
ICAT
Keywords
Field
DocType
fusion behavior,redundant knowledge,virtual agricultural mobile robot,agricultural intelligence,fruit tree,mobile robot,knowledge base,extracting behavior knowledge,behavior knowledge,rough sets systematically,association rule,virtual environment,knowledge extraction,rough set,obstacle avoidance
Virtual machine,Computer science,Expert system,Rough set,Artificial intelligence,Knowledge extraction,Knowledge engineering,Knowledge base,Robot,Mobile robot
Conference
Volume
ISSN
ISBN
4282
0302-9743
3-540-49776-5
Citations 
PageRank 
References 
1
0.46
4
Authors
5
Name
Order
Citations
PageRank
Xiangjun Zou1298.20
Jun Lu210.46
Lufeng Luo372.62
Xiwen Luo4127.61
Yanqiong Zhou510.46