The Research And Development Of Mobile Robot Visual Location System

In recent years,autonomous mobile robot technology has played an increasingly important role in the fields of industry,medicine and social service,which has become a hot topic in the research of international robotics,especially the driverless car has attracted many attention.In the research of autonomous technology of mobile robot,navigation technology is its core technology.Navigation refers to the mobile robot through the sensor to perceive the environment and its own state,to achieve autonomous movement in the unfamiliar environment.Navigation mainly solves three problems,including determining the position of the robot itself,establishing a map of the environment,and finding an optimal or near optimal path for the robot from the current position to the target location.In other words,navigation technology is divided into three blocks: localization,perception and planning.The object of this paper-the visual location system is mainly to solve the robot navigation the first question that to determine the robot's position in the environment.The localization problem is the problem that the autonomous mobile robot determines its position in the working environment,it can be said to be the most important problem in robot navigation technology,because the other two issues based on the localization problem.Recently,with the improvement of the computer performance and the cost of the visual sensor continue falling make the visual localization system been widely used in mobile robotics field.Compared to the traditional positioning method,example wifi localization or bluetooth localization,the visual localization system has the advantages of low cost,high precision and good robustness.In this paper,a series of research on the three key issues of real-time,robustness and high precision are carried out with the aim of high precision and real-time positioning of indoor mobile robot.The main contents are as follows:First,in order to improve the accuracy of the visual location system,the image is segmented in the stage of feature extraction,so that the extracted feature points are distributed evenly in the image.Secondly,in order to improve the robustness of the whole system to noise,the RANSAC algorithm is used to filter out the misalignment caused by noise,so that the system can still run in a relatively low signal to noise ratio.Finally,in order to improve the real-time performance of the system,we choose to extract the feature points.At the same time,the number of iterations of the RANSAC algorithm is greatly reduced by introducing the kinematic constraints of the planar mobile robot.Making the real-time system greatly enhanced.