Research On Robot Positioning Technology Based On Multi-sensor Information Fusion

In recent years,with the rapid development of artificial intelligence,robotics,advanced sensor technology,intelligent control,pattern recognition and other disciplines,intelligent mobile robots have become a hot topic for domestic and foreign research teams and university laboratories.One of the important capabilities of smart mobile robots is autonomous navigation in a strange environment.This is one of the important signs of robot intelligence.In order to complete the autonomous navigation task in a strange environment,the mobile robot must determine its own position in the environment.Determining the position requires acquiring environmental information through the sensor,and using the information of multiple sensors to fuse with each other can provide the mobile robot with more abundant environmental information so that the mobile robot can achieve accurate positioning.The research content of this paper is mainly focused on the positioning problems of mobile robots in the static environment of indoor fusion laser rangefinder and odometer information.The main research content is as follows:First,the research significance and development status of mobile robots,robot positioning technology and information fusion technology are introduced.The mobile robot platform was set up and the control system was designed and debugged so that the mobile robot can achieve all-round movement within the plane.Second,the omnidirectional mobile robot kinematics model,odometer model and laser range finder model were established.The flow of the extended Kalman filter algorithm is analyzed,and the focus is on the use of information from the extended Kalman filter fusion odometer and laser range finder to carry out actual positioning experiments on mobile robots and to record the data of time,odometer data,laser range finder used in the movement process.Finally,the mobile robot positioning experiment of laser rangefinder and odometer information fusion is designed.The experimental results show that(1)the cumulative error of using odometer positioning will increase with the robot's moving distance.(2)Based on the extended Kalman filter algorithm applied in the positioning system of this paper effectively solves the problem of cumulative error of the odometer.(3)The use of laser range finder and odometer information fusion positioning is superior to the odometer only positioning effect,improving the positioning accuracy.