文献类型：会议论文

英文题名：Dynamic collision avoidance path planning for mobile robot based on multi-sensor data fusion by support vector machine

作者：Tian, Jingwen[1];Gao, Meijuan[1];Lu, Erhong[2]

通讯作者：Tian, JW[1]

机构：[1]Beijing Union Univ, Dept Automat Control, Beijing, Peoples R China;[2]Beijing Elect Sci & Technol Inst, Elect & Informat Engn Dept, 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, Dept Automat Control, 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：IEEE International Conference on Mechatronics and Automation

会议日期：AUG 05-08, 2007

会议地点：Harbin, PEOPLES R CHINA

语种：英文

外文关键词：mobile robot; path planning; dynamic collision avoidance; support vector machine; multi-sensor data fusion

摘要：Statistical learning theory is introduced to movement planning of intelligent robot, considering the issues that the dynamic collision avoidance planning of mobile robot is a complicated and nonlinear system, and combine the advantages of the support vector machine (SVM) possessed, a method of mobile robot dynamic collision avoidance planning based on multi-sensor data fusion by SVM is presented in this paper. We utilize 5 ultrasonic sensors and an image sensor get environmental information in this method, and the SVM is used to do multi-sensor data fusion to compute these information, in order to achieve the purpose that dynamic control the mobile robot's next action. The method fully utilizes the potential of the SVM and the multi-sensor data fusion to solve dynamic path planning problem of mobile robot. The simulation result shows that this method is feasible and effective.