关键词：机器人；自动控制系统；定位；交互多模型
摘 要：To investigate robot Simultaneous Localization and Mapping (SLAM) in the unknown environment, the non-linear Interacting Multiple Model (IMM) SLAM algorithm is applied to solve the problem concerning the statistical property mutation of a system. The key point of this algorithm is to use non-linear Gaussian model to approximate non-linear and non-Gaussian model so that robot Simultaneous Localization and Mapping can be achieved. Each model employs the Extended Kalman Filter (EKF) algorithm to linearize the non-linear system and uses the non-linear Interacting Multiple Model algorithm in each step to get fusion estimated value. The Monte Carlo simulation results show that the proposed algorithm has better estimate precision.