Relative Position Based Distributed Localization In 2D Space

With the popularity of wireless electronic devices,determining the location of these devices has become very important.Generally,localization refers to the process of obtaining the geographic location of devices in an area.Localization can be divided into outdoor localization and indoor localization.Outdoor localization mainly relies on GPS,which can provide us with very accurate position information.However,in large cities and indoor environments,there are many obstacles that cause GPS signals to be blocked,and inaccurate localization may occur.In a large factory,if you want to carry out production activities,it is a feasible method to obtain your own location with the help of artificial landmarks.However,most of the current methods for determining the position of artificial landmarks are manual measurement.Because human fatigue will inevitably cause measurement errors during manual measurement,which will seriously affect the localization accuracy.This thesis is based on the To F ranging principle,using a mobile robot loaded with lidar,using lidar to obtain indoor environment information,can obtain high-precision distance and angle information,and control the mobile robot to move indoors to avoid the interference of uncertain factors in the environment during the measuring process.The artificial landmark used in this thesis is reflective column.The main research content is divided into the following two aspects:(1)Sequential indoor localization algorithm based on mobile robot.Before the implementation of the algorithm,it is necessary to arrange reflective columns reasonably in the room,that is,the mobile robot must observe at least three reflective columns at any time,and let the upper controller plan the path of the mobile robot in the room.Based on the principle of To F,the algorithm obtains indoor environment information with the help of lidar.Based on the high-frequency environment detection of the mobile robot,the mobile robot will not move too much between the current time and the last time.The current global coordinate of the mobile robot is calculated through the reflective columns repeatedly detected at the current time and the last time.Based on the correspondence of reflective column between the current time and the previous time,the rotation matrix and the translation matrix between the current local coordinate system and the global coordinate system is calculated,so that the local coordinates of the reflective columns in the current local coordinate system are transformed into the global coordinates.Through the mobile robot moving on the pre planned path controlled by the upper controller,the position information of reflective columns on the path can be obtained in turn,and the indoor reflective column localization can be realized.(2)Distributed indoor localization algorithm based on relative position.Before the implementation of the algorithm,it is also necessary to reasonably arrange the reflective column in the room,and let the upper controller plan the trajectory of the mobile robot in the room.Based on the lidar carried by the mobile robot,the algorithm obtains the surrounding environment information of its location and identifies the reflective column in the environment.Based on the high frequency environment detection of the mobile robot,the reflective column detected repeatedly at the current moment and the previous moment is identified.Based on the lidar information obtained by mobile robot,the complex centroid equation of reflective column is established to store the relative position information between reflective columns.With the help of the moving mobile robot,using the established complex center of mass equations to construct the graph model of the indoor reflective column.Then,the complex Laplace matrix is established,and the distributed localization algorithm is iteratively solved to obtain the position of the indoor reflective columns.