Research On Construction Of Indoor Robot Semantic Map Based On Ontology

Because of the increasingly prominent market for mobile machines and The matures of mobile robot research,the mobile relevant research has aroused widespread concern recently.When robot serves the indoor environment and become a family assistant, those whom with low intelligence on former industrial robots will no longer meet market demand.If we want to make the indoor mobile service robots reach real smart,We should need the robot can perceived indoor environment so it can make intelligent decision.the accuracy and completeness of the perception for indoor decide the accuracy of the robot intelligent decision.As we can know the perception of the indoor environment includes robot itself pose acquisition and construction of the indoor environment map. SLAM(Simultaneous Localization And Mapping,SLAM) be able to solve this problem.But the maps constructed by SLAM only contains the robot’s pose and the environment’s characteristics map,witch is Incomplete because of it isn’t containing indoor environment temperature and environment object attributes as well as other information etc..This leads to the perception of robot the environment is not complete, this is not entirely make the robot can only autonomously navigate but can’t make intelligent decision.Based on SLAM,The author of this paper propose to use the low-power ZigBee get indoor environment data, which will fill in the missing part of the whole SLAM data.At the same time, The author introduces philosophical category’s ontological, to use the ontology language (OWL) on the indoor field witch can Ontological the Heterogeneous objects of the indoor area.The author wishes to use the ontology to convert the heterogeneous environment information.At the same time with the simultaneous inference ontology,building a Semantic Simultaneous Localization And Mapping, referred SSLAM,witch can provide a effective premise for robot intelligent decision.Specifically, this paper is divided into five main modules.1)Introduction. the author has made a brief introduction of the research background and significance of the subject. 2)The research of SLAM. the author introduces the building SLAM map platform’s technologies and principles, and then build the SLAM simulation experiments;3)Indoor environment data acquisition based on ZigBee. the author mainly makes of description of the method to access other environmental factors witch uses to establish SSLAM map.Then make an experiment get some data from the actual environment.First author made a brief introduction for the ZigBee,then is the details the overall process utilizes of ZigBee network data collection, finally the author gives the results of the actual experiment;4)The ontology semantic model of SSLAM. firstly the author make a detail description for building the SSLAM, after that how to build the ontology has bean given.Finally, based on the above authors propose the framework mechanism and semantics of converting ontology data to ontology semantic.5)The Construction Of Intelligent Robot SSLAM. the author has made a simple realization of SSLAM on a real indoor, which mainly includes SLAM acquisition, access to environmental data, and build and data ontology semantic data and the converting between ontology semantic mapping.Finally, in the conclusion, the author considers to build SSLAM indoor mobile robots is a leap of progress, achieving this step the robot will be installed on a thinking mind, although, it may be a bit clumsy mind, but it is a beginning of showing its intelligence.