JOURNAL BROWSE
Search
Advanced SearchSearch Tips
A Study for Color Recognition and Material Delivery of Distributed Multi Vehicles Using Adaptive Fuzzy Controller
facebook(new window)  Pirnt(new window) E-mail(new window) Excel Download
 Title & Authors
A Study for Color Recognition and Material Delivery of Distributed Multi Vehicles Using Adaptive Fuzzy Controller
Kim, Hun-Mo;
  PDF(new window)
 Abstract
In this paper, we present a collaborative method for material delivery using a distributed vehicle agents system. Generally used AGV(Autonomous Guided Vehicle) systems in FA require extraordinary facilities like guidepaths and landmarks and have numerous limitations for application in different environments. Moreover in the case of controlling multi vehicles, the necessity for developing corporation abilities like loading and unloading materials between vehicles including different types is increasing nowadays for automation of material flow. Thus to compensate and improve the functions of AGV, it is important to endow vehicles with the intelligence to recognize environments and goods and to determine the goal point to approach. In this study we propose an interaction method between hetero-type vehicles and adaptive fuzzy logic controllers for sensor-based path planning methods and material identifying methods which recognizes color. For the purpose of carrying materials to the goal, simple color sensor is used instead vision system to search for material and recognize its color in order to determine the goal point to transfer it to. The proposed method reaveals a great deal of improvement on its performance.
 Keywords
Adaptive Fuzzy Controller;Intelligent Vehicle;Material Flow Automation;Distributed Control System;Color Recognition;
 Language
Korean
 Cited by
 References
1.
Do-Yoon Kim, 1996, 'On-Line Path Planning for Multiple Mobile Robots,' MEE 953050, pp. 3-10

2.
C.O'dunlaing, M.Sharir, and C.Yap, 1983, 'Retraction : A new Approach to Motion Planning,' pp. 207-220

3.
Keitarou Naruse and Yukiniri Kakazu, 1994, Rule Generation by Inductive Decision Tree and Reinforcement Learning,' Distributed Autonomous Robotic Systems, Vol. 1 Springer-Verlag Tokyo, pp. 91-95

4.
K.Ozaki, H.Asama, H.Itakura, A.Matsumoto, Y.Ishida and I.Endo, 1991, 'Collision Avoidance among Multiple Mobile Robots Based on Rules and Communication,' Proc. of IEEE/RSJ Int. Workshop on IROS, pp. 1215-1220

5.
Zhi-Dong Wang, H.Asama, and A.Matsumoto, 1989, 'Design of an Autonomous and Distributed Robot System,' Proc. of IEEE/RSJ Int. Workshop on IROS '89, pp. 283-290

6.
Lynne, E. Parker, 1998, 'Alliance: An Architecture for Fault Tolerant Multirobot Cooperation,' IEEE Transactions on Journal of Robotics and Automation, Vol. 14, No. 2, April, pp. 220-228 crossref(new window)

7.
R.Alami, S.Fleury, M.Herrb, F.Ingrand, and F.Robert, 1998, 'Multi-Robot Cooperation in the MARTH project,' IEEE Robotics & Automation Magazine, March, pp. 36-43

8.
S. B. Marapane, Mohan, M. Trivedi, and Nils Lassiter, 1996, 'Motion Control of cooperative Robotic Teams Through Visual Observation and Fuzzy Logic Control,' Proc. of the 1996 IEEE International Conference on Robotics & Automation, Minneapolis, April Vol. 2, pp. 1738-1743

9.
T.C.Lueth, and T.Laengle, 1995, 'Managing Different Types of Interactions Among Robots,' IEEE International Conference on Robotics and Automation, pp. 1503-1508

10.
이종락, 1995,'광센서와 그 사용법,' 세화출판사