Design of Autonomous Navigation System Based on Affective Cognitive Learning and Decision-making

摘要：

A new autonomous navigation control system is presented for mobile robots based on the affective cognitive learning and decision making (ACLDM) model. The behaviors of robot navigation are designed by dynamic system approach, which has a sound theoretical foundation for the system stability analysis. Cognitive states for work environment of the mobile robot are gotten from a pattern classifier based on Adaptive Resonance Theory-2 (ART-2) network. Then rational strategies for behaviors coordination are developed by on-line affective cognitive learning. This control strategy can make the mobile robot navigate autonomously in unknown environment. The designed behaviors can guarantee that the robot navigates safely by choosing an appropriate velocity. Simulation studies have demonstrated that the integration of the affective system with cognitive system can speed up the learning process, and the proposed strategy can effectively improve the capability of robots autonomous navigation.

作者: Huidi Zhang Shirong Liu

作者单位: Ningbo Institute of Technology,Zhejiang University,Ningbo 315100,China Hangzhou Dianzi University ,Xiasha,Hangzhou 310018,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: 2491-2496

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）