• Journal of the Korea Society for Simulation
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• v.17 no.2
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• pp.91-103
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• 2008

In order to simulate the behavior of automated manufacturing systems, the performance of material handling systems should be measured dynamically. Multi-Agent technology could be well adapted for the development of simulator for distributed and intelligent manufacture systems. A multi-agent system is composed of one coordination agent and multiple application agents. Issues in AGVS simulator can be classified by the set-up and operating problems. Decisions on the number of vehicles, bi- or uni-directional guide-path, etc. are fallen into the set-up problem category, while deadlock tree algorithm and conflict resolution are in operating problem. In this paper, a multi-agent based deadlock-free simulator for automated guided vehicle system(AGVS) are proposed through the use of multi-agent technologies and the development of deadlock-free algorithm. In this AGVS simulator proposed, well-known Floyd algorithm is used to create AGVS Guide path, through which AGVS move. Also, AGVs avoid vehicle conflict and deadlock using check path algorithm. And Moving vehicle agents are operated in real-time control by coordination agent. AGV position is dynamically calculated based on the concept of rolling time horizon. Simulator receives and presents operating information of vehicle in AGVS Gaunt chart. The performance of the proposed algorithm and developed simulator based on multi-agent are validated through set of experiments.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.2036-2041
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• 2005

The underwater multi-agent technology has many potential for the various activities related to ocean development/conservation in the near future. For example, in such fields as water pollution investigation, aquaculture control, or coral reef research, we feel a growing need for a system that realizes underwater continuous monitoring in the wide rang e. In this case, the target monitoring area will be sliced planar hierarchically toward the depth as monitoring layers, and many AUVs arranged on each layer track the given trajectory and gather various environmental information continuously, with communicating each other in the layer or with other layers. To realize those systems we need to develop AUV multi-agent technologies. So we are now building basic systems for basin experiment for the development of AUV multi-agent behavior. We must experience many situations and problems to be solved for the development of its elemental technologies by using real systems as well as our computer simulations. In this paper we introduce our concept of the experiment in the near future and the hardware/software design of our two types of handy AUVs and ultrasound ranging/communication system for that experiment. One AUV is designed using a 17inches-diameter glass sphere with DOS/V and RT-Linux based subsystems, which is intended to use not only in the basin but also in the calm real sea. The other AUV is designed for the basin experiment using a 7inches-diameter acrylic sphere with low-cost embedded system with SH-2 based subsystems. The basin experiment to verify the basic AUV facilities and ultrasound ranging for position detection was carried out.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.164.1-164
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• 2001

Q-learning is a recent reinforcement learning algorithm that does not need a modeling of environment and it is a suitable approach to learn behaviors for autonomous agents. But when it is applied to multi-agent learning with many I/O states, it is usually too complex and slow. To overcome this problem in the multi-agent learning system, we propose the successive Q-learning algorithm. Successive Q-learning algorithm divides state-action pairs, which agents can have, into several Q-functions, so it can reduce complexity and calculation amounts. This algorithm is suitable for multi-agent learning in a dynamically changing environment. The proposed successive Q-learning algorithm is applied to the prey-predator problem with the one-prey and two-predators, and its effectiveness is verified from the efficient avoidance ability of the prey agent.

• Journal of information and communication convergence engineering
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• v.17 no.3
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• pp.167-173
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• 2019

This study investigates the problem of leader-following consensus for multi-agent systems with output saturations. This study assumes that the agents are described as a neutrally stable system, and the leader agent generates the bounded trajectory within the saturation level. Then, the objective of the leader-following consensus is to track the trajectory of the leader by exchanging information with neighbors. To solve this problem, we propose an observer-based distributed consensus algorithm. Then, we provide a consensus analysis by applying the Lyapunov stability theorem and LaSalle's invariance principle. The result shows that the agents achieve the leader-following consensus in a global sense. Moreover, we can achieve the consensus by choosing any positive control gain. Finally, we perform a numerical simulation to demonstrate the validity of the proposed algorithm.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2001.01a
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• pp.145-150
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• 2001

A Controlled Ecological Life Support System(CELSS) is essential for man to live a long time in a closed space such as a lunar base or a mars base. Such a system may be an extremely complex system that has a lot of facilities and circulates multiple substances,. Therefore, it is very difficult task to control the whole CELSS. Thus by regarding facilities constituting the CELSS as agents and regarding the status and action as information, the whole CELSS can be treated as multi-agent system(MAS). If a CELSS can be regarded as MAS the CELSS can have three advantages with the MAS. First the MAS need not have a central computer. Second the expendability of the CELSS increases. Third, its fault tolerance rises. However it is difficult to describe the cooperation protocol among agents for MAS. Therefore in this study we propose to apply reinforcement learning (RL), because RL enables and agent to acquire a control rule automatically. To prove that MAS and RL are effective methods. we have created the system in Java, which easily gives a distributed environment that is the characteristics feature of an agent. In this paper, we report the simulation results for material circulation control of the CELSS by the MAS and RL.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.2023-2028
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• 2004

This paper reveals the utilization of the multi-gent system that based on the Blackboard system basis as the controller of Soccer Robot. This system is a portion of developing the Soccer Robot team for Robocup 2004 Competition. In this development, the intelligent control system was initiated by the combination of parallel and distributed blackboard structures with the principle design that generated from human body structures, which consists of the combination of two main systems, the organs system and the brain system. The system is designed using the control system theory based on Blackboard basis. Modification of the initial structures to corroborate the Soccer Robot and the structure's constituents are clarified accordingly. To demonstrate the idea, ITE-old team is given as a case study.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.5
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• pp.390-397
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• 2013

This paper presents a consensus algorithm for uMAS (uncertain Multi-Agent Systems). Unlike previous results in which only nominal models for agents are considered, it is assumed that the uncertain agent model belongs to a known polytope set. In the middle of deriving the proposed algorithm, a convex set is found which includes all uncertainties in the problem using convexity of the polytope set. This set plays an important role in designing the consensus algorithm for uMAS. Based on the set, a consensus condition for uMAS is proposed and the corresponding consensus design problem is solved using LMI (Linear Matrix Inequality). Simulation result shows that the proposed consensus algorithm successfully leads to consensus of the state of uMAS.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.896-902
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• 2004

The purpose of the study of multi-robot system is to realize multi-robot system easy for the control of robot system in case robot is adapted in the complicated environment of task structure. The purpose of the study of multi-robot system is to realize multi-robot system easy for the control of robot system in case robot is adapted in the complicated environment of task structure. To make real time control possible by making effective use of recognized information in this dynamic environment, suitable distribution of tasks should be made in consideration of function and role of each performing robots. In this paper, IHMA (Intelligent Hybrid Modular Architecture) of Intelligent combined control architecture which utilizes the merits of deliberative and reactive controllers will be suggested and its efficiency will be evaluated through the adaptation of control architecture to representative multi-robot system.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.608-611
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• 1997

The soccer robot system consists of multi agents, with highly coordinated operation and movements so as to fulfill specific objectives, even under adverse situation. The coordination of the multi-agents is associated with a lot of supplementary work in advance. The associated issues are the position correction, prevention of communication congestion, local information sensing in addition to the need for imitating the human-like decision making. A control structure for soccer robot is designed and several behaviors and actions for a soccer robot are proposed. Variable zone defense as a basic strategy and several special strategies for fouls are applied to SOTY2 team.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.48 no.8
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• pp.573-580
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• 2020

One of challengeable problems of multi-agent systems is a positioning control. Augmented Cucker-Smale model is using for controlling position and velocity of the multi-agent system. The original model applies same coefficients to all agents in same group, so that does not consider characteristic of each agent. To enhance performance of the original model, this paper transforms original coefficients to Mahalanobis distance coefficients that reflects an initial distribution of multi-agent systems and applies statistical degrees of freedom. This paper not only confirms tendency of enhanced performance of the suggested model by using monte-carlo simulation, but also additionally compares trajectory of the original model with the suggested model to confirm coefficients of Mahalanobis distance performing correctly.