In order to solve the problem of poor robustness of Simultaneous Localization and Mapping (SLAM) to noise interference and motion trajectory prediction error in complex environment,the adaptive estimation theory and robust H∞ control criterion are introduced into UKF,and a robust adaptive UKF-SLAM algorithm is proposed.The algorithm uses adaptive estimation theory to construct the robust factor and the adaptive factor,adaptively estimates the equivalent covariance matrix of measurement and state noise,and realizes coarse error separation and adaptive compensation of noise variance.The robust H∞ control criterion is used to iteratively update the system state mean and covariance to improve the robustness to noise interference and reduce the prediction error.Simulation results show that the algorithm can ensure that the mobile robot has good robustness and positioning accuracy in different noise environment.