摘要： 针对有色量测噪声模型，提出一种有色量测噪声下的轮式机器人同步定位与地图构建算法。通过重新组合轮式机器人的过程模型和量测模型，将有色量测噪声量测模型转化为虚拟的白噪声量测模型。为使过程噪声和量测噪声不相关，对过程模型进行不相关条件处理。算法按照构造的虚拟过程模型和量测模型进行滤波估计和地图构建。仿真结果验证了算法的一致性和鲁棒性。

关键词: 有色量测噪声, 轮式机器人, 同步定位与地图构建, 算法一致性

Abstract: Aiming at colored measurement noise model, this paper presents a Simultaneous Localization and Mapping(SLAM) algorithm for wheeled robot under colored measurement noise. Colored measurement noise model is converted into white measurement noise model by recombining the process model and the measurement model for wheeled robot. In order to make the process noise and the measurement noise irrelevant each other, the process model is re-defined. Estimating state and mapping are conducted in accordance with the virtual process model and the virtual measurement model. In data association step, part observed landmarks are processed as redundant landmarks. Some indicators of the filter are used to evaluate the performance the algorithm. Simulation results show that the algorithm is consistent and robust.

Key words: colored measurement noise, wheeled robot, Simultaneous Localization and Mapping(SLAM), consistency of algorithm

中图分类号: 

• TP242