Mobile Robot Behavior Controller Based on Genetic Diagonal Recurrent Neural Network

摘要：

It is crucial that a robot should have both learning and evolutionary ability to adapt to dynamic environments. This paper proposes a new mobile robot behavior controller based on genetic algorithm (GA) and diagonal recurrent neural network (DRNN). The DRNN has the advantages of time series prediction capability because of its memory nodes, as well as local recurrent and self- feedback connections. Genetic algorithm is introduced to optimize the learning rate and the structure of DRNN in order to achieve better performance. Finally, the GA-DRNN is applied to the mobile robot behavior controllerSimulation results show that the controller based on GA-DRNN possesses higher precision, compared with controller based on DRNN.

关键词： Diagonal Recurrent Neural Network (DRNN) Genetic Algorithm (GA) Mobile Robot Behavior Controller

作者: Yanchun Du Yibin Li Guiyue Wang

作者单位: Postdoctoral Station of Mechanical Engineering Shandong University Jinan, Shandong Province, China School of Control Science and Engineering Shandong University Jinan, Shandong Province, China School of Information Management Shandong Economic University Jinan, Shandong Province, China

会议类型: 国际会议

会议名称: 2007 IEEE International Conference on Automation and Lofistics

会议地点: 山东济南

会议语种:英文

在线出版日期: 2007-08-18（万方平台首次上网日期，不代表论文的发表时间）