An Intelligent Cooperative System Using Fuzzy Instruction for Car-Like Driving

An impedance controller using fuzzy instruction to support human’s operation in human-vehicle interaction is studied in this paper. Fuzzy instruction is a fuzzy set of control instruction candidates and is composed of satisfaction rating as membership value with the candidates. In order to examine the support performance of impedance controller, an effective car-like driving training system is established, and an intelligent cooperative system using fuzzy instruction is constructed. The intelligent cooperative system is applied to the training system to help trainee learn driving a vehicle safely, availably and quickly. The experimental results demonstrate that the intelligent cooperative system cooperates with trainee’s operation according to the surrounding variation situation, and does adaptive support flexibly on a wide/narrow road through the car-like driving training system.

[1]  Shenghao Zhou,et al.  A Cooperative Auto-driving System Based on Fuzzy Instruction , 2006 .

[2]  S. Yasunobu,et al.  An intelligent cooperative control system based on predictive fuzzy control , 2004, SICE 2004 Annual Conference.

[3]  Ryojun Ikeura,et al.  Optimal variable impedance control for a robot and its application to lifting an object with a human , 2002, Proceedings. 11th IEEE International Workshop on Robot and Human Interactive Communication.

[4]  Homayoon Kazerooni,et al.  The human power amplifier technology at the University of California, Berkeley , 1996, Robotics Auton. Syst..

[5]  R. Riener,et al.  Human-centered robotics applied to gait training and assessment. , 2006, Journal of rehabilitation research and development.

[6]  Seiji Yasunobu,et al.  An Intelligent Cooperative Control System Based on Fuzzy Instruction , 2005 .

[7]  Homayoon Kazerooni,et al.  Human/robot interaction via the transfer of power and information signals , 1989, Images of the Twenty-First Century. Proceedings of the Annual International Engineering in Medicine and Biology Society,.

[8]  Kazuo Tanaka,et al.  Fuzzy control systems design and analysis , 2001 .

[9]  Yoshiyuki Tanaka,et al.  Tracking control properties of human-robotic systems based on impedance control , 2005, IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans.