A hierarchical fuzzy steering controller for mobile robots

被引:0
作者
Teiner, M [1 ]
Rojas, I [1 ]
Goser, K [1 ]
Valenzuela, O [1 ]
机构
[1] Univ Dortmund, Dept Elect Engn Microelect, D-44221 Dortmund, Germany
来源
CIMSA'03: 2003 IEEE INTERNATIONAL SYMPOSIUM ON COMPUTATIONAL INTELLIGENCE FOR MEASUREMENT SYSTEMS AND APPLICATIONS | 2003年
关键词
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This paper describes a hierarchical fuzzy steering controller approach to local navigation of an autonomous sensor equipped mobile robots. Two goals are considered simultaneously: obstacle avoidance, so that the robot is piloted safely in an unknown environment; and reaching an target point. A two-step approach to build a fuzzy system is presented In the first stage signals are processed by conventional methods to get an output vector indicating the direction and the closeness of obstacles around Stage two is a basic task steering controller, that is based on fuzzy logic. The modular structure of the first stage allows modifications on the robot. So there is no need for a redesign of the controller's architecture, when the controller is used in different applications. Adaptation to a new task is done simply by adjusting the controller to other conditions. Then the robustness of this controller is demonstrated in simulations by means of erroneous signals of the sensor modules. Finally the controller is used in combination with another basic task controller for 'Reaching an Aiming Point'. In a higher level a controller ascertains priority of the controllers and manages the resulting steering commands.
引用
收藏
页码:7 / 12
页数:6
相关论文
共 12 条
[1]   Soft comuting for autonomous robotic systems [J].
Akbarzadeh, MR ;
Kumbla, K ;
Tunstel, E ;
Jamshidi, M .
COMPUTERS & ELECTRICAL ENGINEERING, 2000, 26 (01) :5-32
[2]  
GLORENNEC PY, REINFORCEMENT LEARNI
[3]   Evolutionary algorithms for fuzzy control system design [J].
Hoffmann, F .
PROCEEDINGS OF THE IEEE, 2001, 89 (09) :1318-1333
[4]   Evolutionary design of a fuzzy knowledge base for a mobile robot [J].
Hoffmann, F ;
Pfister, G .
INTERNATIONAL JOURNAL OF APPROXIMATE REASONING, 1997, 17 (04) :447-469
[5]   SIMULTANEOUS DESIGN OF MEMBERSHIP FUNCTIONS AND RULE SETS FOR FUZZY CONTROLLERS USING GENETIC ALGORITHMS [J].
HOMAIFAR, A ;
MCCORMICK, E .
IEEE TRANSACTIONS ON FUZZY SYSTEMS, 1995, 3 (02) :129-139
[6]  
HOMAIFAR A, SOFT COMPUTING BASED
[7]  
MARTINALVAREZ A, FUZZY REACTIVE PILOT
[8]   New methodology for the development of adaptive and self-learning fuzzy controllers in real time [J].
Rojas, I ;
Pomares, H ;
Pelayo, FJ ;
Anguita, M ;
Ros, E ;
Prieto, A .
INTERNATIONAL JOURNAL OF APPROXIMATE REASONING, 1999, 21 (02) :109-136
[9]   Behavior-based robot navigation on challenging terrain: A fuzzy logic approach [J].
Seraji, H ;
Howard, A .
IEEE TRANSACTIONS ON ROBOTICS AND AUTOMATION, 2002, 18 (03) :308-321
[10]  
SIRIPUN TC, 2002, P AM CONTR C, P995