基于灰色定性理论的移动机器人地图创建

Map building for mobile robot based on GQSIM

针对移动机器人自主导航地图创建中超声波信息存在不确定性的问题,提出一种新的基于灰色定性理论的超声波信息解释和融合的方法,并用于处理超声波传感器信息和移动机器人创建环境地图.首先,引入概率灰数对超声波信息的不确定性进行描述,以获得栅格单元和传感器的概率灰数模型;然后,设计超声波传感器新旧信息的融合方法,从而得到环境地图的整体表示;最后通过地图创建仿真实验结果表明了这种方法具有良好的鲁棒性和准确度.

According to the uncertainty of sonar information in map building of mobile robot autonomous navigation, a novel method based on grey qualitative simulation（GQSIM） is proposed to interpret and combine sonar information, which is used to process sonar information and build grid map of the environment. First, probability grey number is introduced to describe the uncertainty of sonar information, in order to obtain the probability grey number models of grid cell and sonar. Then, a fusion method is devised to combine new and old information, so that the global map of the enviroment is built： Finally, simulation experiment results show the robustness and accuracy of the proposed method.