Abstract: This paper presents an innovative method to estimate the position of mobile robot with 5G “broadband cloud information” visual image processing aided by BDS,so as to eliminate errors to improve accuracy.By improving the Pyramid LK algorithm to estimate the optical flow velocity,the mobile robot speed can be accurately obtained,and the acceleration value is providedby the mobile phone acceleration sensor,and the three-dimensional position information of the mobile robot can be roughly provided by the Beidou receiver.The improved Kalman filter is used for data fusion.The improved path is first supervised by the wavelet neural network.Then the improved gradient descent method is used to study and train the weights and parameters of the wavelet neural network.Finally,the combination algorithm of PSO and GA is further used to correct the weights and thresholds of the wavelet neural network with a view to further improve the performance of Kalman filter and highlight the advantages of the cumulative error of the robot visual positioning method corrected by BDS.It improves the accuracy and reliability of integrated navigation and positioning in special harsh environment,and has important reference value for the in-depth research of BDS and 5G technology in the field of mobile robots.

Key words: Data fusion, Improved Kalman filter algorithm, Mobile robot, Visual image processing