Research On Method And Implementation With Indoor Mapping In Mobile Robot

In the field of robot research,Simultaneous Localization and Mapping(SLAM)technologies are the key to autonomous navigation.As a SLAM method,map creation is of great significance.This thesis makes a deep study on the analysis of key issues for indoor SLAM technology and establishes the solving model of the corresponding problems.At the same time,combining with the practical application,the method of multi-sensor data fusion and laser scan matching are introduced in the robot map building process.Moreover,the =grid reflectivity calculation model is established to update grid state.This method improves the precision and efficiency of robot localization and accuracy of mapping.Finally,we build a robot experimental platform and verify that the improved algorithms are feasible and effective.Aiming at the problem that the inaccurate of robot attitude angle due to the low accuracy of the encoder data,this thesis uses the meth od of Extended Kalman Filter to fuse encoder data and gyroscope data,this can improve the accuracy of measurement about robot pose and ensure the effectiveness of the algorithm’s implementation.Aiming at the problem that the robot pose is inaccurate caused by the accumulated error of mileage in the traditional odometer localization method,in this paper,we use scan-matching algorithm to estimate the relative pose transformation between two consecutive measurements,so as to effectively correct the odometer positioning results and improve the accuracy of the ro bot’s long distance positioning.Aiming at the problem that the traditional method of Grid Mapping is complex and the edge of the map is poor,this paper use the method of grid reflectivity calculation to update the probability of grid and improve the accuracy and computational efficiency.In order to verify the practicability and feasibility of the proposed algorithm described in this paper,an actual robot experiment platform is built to implement the SLAM function,and its effectiveness is verified by the experimental data analysis.