Research On Indoor Positioning Method Of Robot Based On RFID

With the rapid development of Internet technology and the continuous improvement of people's living standard,the intelligent home is more and more popular,the robot plays an important role in intelligent Home,it can achieve a variety of functions,such as delivering things and opening windows.The robot has precise requirements for indoor positioning.At present,the outdoor positioning technology,GPS global satellite navigation positioning system has been very mature,but the indoor environment is more complicated,the signal is affected by the multipath effect and non-line-of-sight effect,it is difficult to achieve indoor positioning.Therefore,this paper studies the indoor positioning method of the robot based on RFID.By analyzing and studying the existing RFID indoor positioning technology,this paper improves RFID indoor positioning technology from hardware,software and algorithm.Firstly,proposing Cross distribution strategy of tags.In the experimental environment,a vertical tag is placed at a certain distance,and a lateral tag is placed in the middle of the four longitudinal tags,which solves the problem of the direction of the tag to the receiving signal of the reader.Secondly,the original signal acquisition system of the reader can only read tags' basic information and the immediately Received Signal Strength Indication(RSSI),after secondary development,it can read the tags and their corresponding coordinates and the average value of RSSI.Through the analysis of the experimental results,the Positioning accuracy of using Maximum Likelihood Estimate Positioning(MLEP)method greatly improved by using the the average value of RSSI.Finally,proposing the particle swarm optimization-maximum likelihood estimation method(PSO-MLEP),this method aims at the low accuracy of MLEP,convert the MLEP method to solving the minimum value of the function,and then the PSO is used to solve the minimum value problem.Experimental results show that the algorithm can significantly improve the positioning accuracy of the indoor positioning of the robot,the average positioning error is about 3cm,compared with the traditional location algorithm's about 12 cm average positioning error,the positioning accuracy is improved nearly 3 times.