Research On Indoor Location Method Of Intelligent Car Based On Wireless Sensor Network

In recent years,with the rapid development of Internet and artificial intelligence technology,more and more innovative technology is being developed.The wireless sensor network(WSN)and intelligent robot are both of them,and they have become a research hotspot in the era of Internet plus.The research of intelligent robot under the WSN has also become the objects of many researchers,the combination of them is an innovation,too.There are a large number of sensor nodes in the WSN.If the robot used as a mobile node of the sensor network,the robot will get more environmental information and provide data to support robot decision.And the sensor network can also upload the dynamic information collected by the robot,then enrich the environment letter of the customer detection area.So the customer could make batter decision.As the common problem of these two technologies,position is an urgent problem to be solved at the mome nt.In this paper,the node location method of WSN was studied,and a simple positioning system was built with the dynamic characteristics of the mobile robot.After analyzing and comparing all kinds of location algorithms,combining with the actual situation,the location algorithm based on RSSI distance measurement was selected.By experiment,the characteristics of the RSSI based distance measurement model were analyzed carefully,and a new positioning strategy was proposed,concerning with the dynamic process of the mobile robot.The main contents and contributions of this paper are summarized as follows:(1)Based on the analysis and comparison of the location methods used in WSN,combining the characteristics of mobile robots,the location method of distance measurement is determined to be more suitable for mobile robots.The wireless RSSI is used as the basis of distance measurement.And the positioning ability of the car in the indoor environment is increased,and the existence of the distance blind area is avoided.(2)Through the collected RSSI data,the error sources and shortcomings of the RSSI distance measurement model are analyzed.In view of the acquired experimental data and the characteristics of RSSI ranging,a method of improving the range model by FIS is proposed,.The fuzzy statistics experiment is carried out,which provides the method support for the selection of membership functions.Experimental results show that the method is effective.(3)Aiming at the problem that the RSSI ranging model is susceptible to environmental interference,the FIS ranging model is optimized.Based on the analysis of the experimental data of distance measurement,the ANFIS algorithm is proposed to establish the FIS distance measurement model.The experiment proves that the method improves the environmental adaptability of the FIS ranging,reduces the calculation and workload of the FIS system by fuzzy statistics.The accuracy of the distance measurement and positioning is improved.(4)A simple positioning system was built by using Arduino UNO3,CC2530 and MATLAB GUI.The whole system includes the improved location algorithm based on RSSI,optimization of vehicle dynamic process,and real-time coordinate display interface.The positioning system lays the foundation for future research.(5)In the practical application,the coordinate system required for positioning is set up,the static and dynamic positioning of the mobile trolley is located.The source of the positioning error is analyzed,and the Calman filter is added to the dynamic process of the car to increase the dynamic positioning accuracy.