Evidence Reasoning Machine Based on DSmT for Mobile Robot Mapping in Unknown Dynamic Environment

摘要：

In this paper a new method of information fusion, Dezert-Smarandache Theory (DSmT) is introduced to deal with high conflicting and uncertain information. And then the Evidence Reasoning Machine (ERM) based on DSmT is presented for mobile robot mapping in unknown dynamic environment. Considering the characteristics of sonar sensors, the grid map method is adopted and a sonar sensor mathematical model is constructed based on DSmT. Meanwhile a few of general basic belief assignment functions (gbbaf) are constructed for fusion. Finally, map building experiment is carried out with Pioneer 2-Dxe mobile robot. The experiment results testify the validity of ERM with DSmT for fusing imprecise information during map building in unknown dynamic environment.

关键词： Mobile robot mapping evidence reasoning Dezert-Smarandache Theory

作者: Xinhan Huang Peng Li Min Wang

作者单位: Department of Control Science and Engineering Huazhong University of Science and Technology Wuhan 430074,China

会议类型: 国际会议

会议名称: 2009 IEEE International Conference on Robotics and Biomimetics(2009 IEEE 机器人与仿生技术国际会议 ROBIO 2009)

会议地点: 桂林

会议语种:英文

页码: 753-758

在线出版日期: 2009-12-19（万方平台首次上网日期，不代表论文的发表时间）