Research And Application Of Indoor Positioning Navigation System

At this stage,robots have been widely used in a wide range of applications,both in the service industry and in individual homes.For small-scale cleaning robots in the home,it is necessary to prevent collision of the walls and clean the corners and walls.For the self-service high-end robotic restaurant,the delivery robot can transport the food from the kitchen to the customer's desk.This requires precise indoor positioning technology and navigation system.If you can give the robot the best indoor positioning and indoor navigation methods,the robot work efficiency will be greatly improved.Based on this background,this paper has carried out a series of application research on indoor autonomous navigation system,including positioning system of indoor infrared fixed beacon,path planning of improved particle swarm algorithm,indoor navigation based on odometer.This article focuses on specific indoor environments.The main contents of work research are:Firstly,an indoor positioning system based on infrared fixed beacon is designed.The positioning system is composed of infrared fixed beacon,mobile robot car receiving camera,controlling vertical and horizontal rotating parts of the camera,and vertical and horizontal angle sensor parts.The infrared fixed beacon is fixed in advance on the indoor wall.Regardless of whether the robot car moves or not,the camera on the robot car always tracks the infrared fixed beacon.After the robot trolley moves,the angle difference between the vertical and horizontal angle values and the system initialization time is read,and the indoor coordinates of the robot trolley are calculated by the angle difference and the position information of the fixed beacon.Secondly,due to the error of the obtained positioning data,the indoor positioning data is processed by the K-grouping error compensation algorithm to obtain more accurate indoor positioning information.The method performs a fusion process on a large number of indoor coordinate positioning points,and performs error compensation on the positioning data,thereby improving the accuracy of the positioning information.Finally,based on the indoor infrared positioning system,the navigation work of the indoor robot car was carried out.Robot navigation refers to the process in which a robot moves from a given starting point to a given end point according to a planned path.Therefore,based on the experimental environment,the experimental path of the robot trolley based on the improved particle swarm optimization algorithm is designed.The odometer navigation model is established,and the cumulative error and cumulative error elimination method in odometer navigation are analyzed.Using the encoder installed on the small wheel of the robot,the overall experimental research of the whole indoor positioning navigation system was carried out according to the odometer navigation method on the already planned path.The analysis of the experimental results shows that the modules of the indoor positioning navigation system meet the requirements of the indoor positioning and navigation system,and the overall experimental results meet the preset standards.This paper provides new ideas and methods for the research of indoor positioning navigation system,which has high reference value and practical significance.