A novel fusion method for robot indoor environment mapping
A novel fusion method for robot indoor environment mapping
复制标题
DOI：
10.1109/robio.2014.7090717
复制
发表时间：
2014-12
期刊：
影响因子：
--
通讯作者：
Huo Guanglei;L. Ruifeng;Zhao Lijun;Wang Ke
中科院分区：
文献类型：
--
作者：
Huo Guanglei;L. Ruifeng;Zhao Lijun;Wang Ke
为了解决移动的机器人地图绘制的稳定性问题，提出了一种基于卡尔曼滤波的融合方法，以减小移动的机器人在运动过程中的累积误差。该融合方法能够将顺序扫描匹配结果与里程计测量值进行融合，适用于基于原始点的扫描匹配方法。本文将基于原始点扫描匹配法的位姿估计结果作为观测模型，里程计测量值作为状态模型。实验结果验证了该方法的有效性。
In order to solve the stability of mapping of mobile robot, a fusion method based on Kalman Filter is proposed to reduce the accumulative errors during the mobile motion. This fusion method, which can fuse the sequential scan matching results and odometer measures, is suitable for raw points based scan matching method. In this paper, pose estimation results from raw points based scan matching method are viewed as the observation model, and odometer measures are viewed as the status model. Experimental results are shown to validate the effectiveness of the proposed approach.