A Grey System Theory Based Mobile Robot Localization Algorithm
High precision and high robust mobile robot localization algorithm is a key technology for indoor SLAM.For decreasing the effect of perception uncertainty, a robot position estimation algorithm based on grey system theory is presented.A grey state model is established to represent the robot position with uncertainty, which is composed of a grey domain and a corresponding whitening function.In the proposed algorithm, the observation and odometer data are fused to estimate the grey domain of the robot”s state and the whitening function is then constructed in a Monte Carlo sampling way according to the observation.The best robot position estimation is the state which corresponds to the maximum value of the whitening function.Experimental results show that the proposed mobile robot localization algorithm can handle the uncertainty information effectively and realize precise, robust robot position estimation.
Localization Grey State Model Whitening Function
Wang Ji-kai Wang Peng Chen Zong-hai
Department of Automation, University of Science and Technology of China,Anhui, Hefei,230027
国内会议
第18届中国系统仿真技术及其应用学术年会(18th CCSSTA 2017)
兰州
英文
324-328
2017-08-01（万方平台首次上网日期，不代表论文的发表时间）