中文摘要：

基于最近提出的一种在贝叶斯和DST扩展而来的信息融合算法DSmT（Dezert—Smarandache Theory），在实验的基础上，结合Sonar测量的基本特性，对静态结构化环境建模，并构造了广义基本信度赋值函数，利用经典DSm融合规则，融合每个栅格的声纳冗余信息，计算栅格占用的Bel。最后，以Pioneer Ⅱ移动机器人作为试验平台，并在线对小型环境进行了3D栅格占用信度分布地图创建，其俯视图与实际2D地图中的物体外观轮廓及所在位置进行比较，其比较结果充分验证了算法的有效性，为进一步研究应用基于折扣理论的DSmT解决异类或同类非可靠多源信息融合，基于Hybrid DSmT的动态环境地图创建，以及多机器人联合创建地图和自定位奠定了坚实的基础。

英文摘要：

A new method of information fusion recently developed from Bayesian theory and Dempster-Shafer theory was applied and on the base of experiment, according to sonar＇ s metrical characteristic, the general basic belief assignment functions were constructed for modeling of static environment. After sonar＇ s redundant information for each grid was fused according to classic DSm rule, the Bel for grid＇ s occupancy was calculated. Finally, Pioneer Ⅱ mobile robot served as the experiment platform, and 3D Map was built based on DSmT on-line respectively. By comparing its planform from objects＇ profile and location in the real 2D environment, the validity of this method was fully verified. In short, would establish a firm foundation for further research on solving heterogeneous or homogeneous multi-source information fusion according to DSmT based on discount theory, on map building in dynamic environment and multi-robot＇ s map building together and self-localization based on Hybrid DSmT.