详细信息
Simulation study on underwater autonomous robot based on fuzzy Kalman filter algorithm ( CPCI-S收录 EI收录)
文献类型:会议论文
英文题名:Simulation study on underwater autonomous robot based on fuzzy Kalman filter algorithm
作者:Yang, Qingmei[1];Sun, Jianmin[1]
第一作者:杨清梅
通讯作者:Yang, QM[1]
机构:[1]Beijing Union Univ, Coll Automat, Beijing, Peoples R China
第一机构:北京联合大学城市轨道交通与物流学院
通讯机构:[1]corresponding author), Beijing Union Univ, Coll Automat, Beijing, Peoples R China.|[1141751]北京联合大学城市轨道交通与物流学院;[11417]北京联合大学;
会议论文集:4th International Conference on Fuzzy Systems and Knowledge Discovery
会议日期:AUG 24-27, 2007
会议地点:Haikou, PEOPLES R CHINA
语种:英文
外文关键词:Algorithms - Data fusion - Fuzzy systems - Information analysis - Kalman filters
摘要:Data fusion methods are widely used in autonomous robots' measurement system in order to acquire more comprehensive and more exact information. Multi-sensor data fusion is to combine multi-sensor's information, which is redundant or complementary in the space or the time to obtain the uniform description or the understanding to the measured object according to a certain criterion. Move-in-mud robot is an autonomous robot, which can excavate hole in the mud underwater. It can be used in sunken wreck salvage to improve the efficiency of excavating the hole. Location system of move-in-mud robot is designed in the paper and location principle of move-in-mud robot is analyzed. Fuzzy Kalman filter arithmetic is applied and simulated in location system of move-in-mud robot to fuse redundant information of the robot. The simulation results show the data fusion method can improve location accuracy.
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