Simultaneous Localization and Mapping of Robot Concerning Statistical Property Mutation

To deal with the problem concerning the statistical property mutation of a system in the unknown environment,a simultaneous localization and mapping(SLAM) algorithm based on non-linear interacting multiple model(IMM) was proposed.It is main idea of the algorithm that non-linear Gaussian model is used to approximate non-linear and non-Gaussian model ;the extended Kalman filter(EKF) algorithm is employed to linearize the non-linear system for each model;the non-linear IMM algorithm is used to get fusion estimated value in each step;SLAM of the robot can be achieved.The Monte Carlo simulation results show that at changing RMSEs of noises of process, observation and both mentioned,the proposed algorithm has better estimate precision compared with EKF-SLAM algorithm and Fast-SLAM algorithm.