• 제어로봇시스템학회논문지
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• 제16권9호
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• pp.898-904
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• 2010

Unmanned autonomous forklifts have a great potential to enhance the productivity of material handling in various applications because these forklifts can pick up and deliver loads without an operator and any fixed guide. There are, however, many technical difficulties in developing such forklifts including localization, map building, sensor fusion, control and so on. Implementation, which is often neglected, is one of practical issues in developing such an autonomous device. This is because the system requires numerous sensors, actuators, and controllers that need to be connected with each other, and the number of connections grows very rapidly as the number of devices grows. Another requirement on the integration is that the system should allow changes in the system design so that modification and addition of system components can be accommodated without too much effort. This paper presents a network-based distributed approach where system components are connected to a shared CAN network, and control functions are divided into small tasks that are distributed over a number of microcontrollers with a limited computing capacity. This approach is successfully applied to develop an unmanned forklift.

• International Journal of Control, Automation, and Systems
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• 제6권2호
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• pp.282-287
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• 2008

In distributed mobile robot systems, autonomous robots accomplish complicated tasks through intelligent cooperation with each other. This paper presents behavior learning and online distributed evolution for cooperative behavior of a group of autonomous robots. Learning and evolution capabilities are essential for a group of autonomous robots to adapt to unstructured environments. Behavior learning finds an optimal state-action mapping of a robot for a given operating condition. In behavior learning, a Q-learning algorithm is modified to handle delayed rewards in the distributed robot systems. A group of robots implements cooperative behaviors through communication with other robots. Individual robots improve the state-action mapping through online evolution with the crossover operator based on the Q-values and their update frequencies. A cooperative material search problem demonstrated the effectiveness of the proposed behavior learning and online distributed evolution method for implementing cooperative behavior of a group of autonomous mobile robots.

• 한국경영과학회지
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• 제24권2호
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• pp.17-29
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• 1999

The manufacturing systems have to cope with the circumstance that the requirements of customers are changed abruptly and the life cycle of product becomes short. In this paper, to develop the efficient control and operation of autonomous, distributed machining systems the concept of Holonic Manufacturing System is adopted and methods for the control and operation of the system are proposed including an evaluation function for the negotiation between holons. And it is applied to scheduling and selection of operations to be worked with consideration of quality. It is expected that the proposed methods may be applied to operate autonomous, distributed machining systems.

• 제어로봇시스템학회논문지
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• 제17권10호
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• pp.1051-1058
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• 2011

Unmanned autonomous forklifts have a great potential to enhance the productivity of material handling in various applications because these forklifts can pick up and deliver loads without an operator and any fixed guide. Especially, automation of pallet loading and unloading technique is useful for enhancing performance of logistics and reducing cost for automation system. There are, however, many technical difficulties in developing such forklifts including localization, map building, sensor fusion, control, and so on. This is because the system requires numerous sensors, actuators, and controllers that need to be connected with each other, and the number of connections grows very rapidly as the number of devices grows. This paper presents a vision sensorbased autonomous loading and unloading for network-based unmanned forklift where system components are connected to a shared CAN network. Functions such as image processing and control algorithm are divided into small tasks that are distributed over a number of microcontrollers with a limited computing capacity. And the experimental results show that proposed architecture can be an appropriate choice for autonomous loading in the unmanned forklift.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1987년도 한국자동제어학술회의논문집; 한국과학기술대학, 충남; 16-17 Oct. 1987
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• pp.29-31
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• 1987

As the conventional manipulators are centralized system, they are considered to have many problems in future because of their wiring and software. For this reason, a rather advanced intelligent manipulator Is not able to realize by using the centralized concept. And this paper describes the manipulator based on autonomous distributed concept to solve the problems.

• 한국산학기술학회논문지
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• 제17권11호
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• pp.1-9
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• 2016

열차제어시스템은 지상 전기 중심에서 차상 통신 중심으로 변화하고 있다. 최신의 열차제어시스템인 CBTC 시스템은 차상과 지상시스템 간 양방향 무선통신을 기반으로 높은 간격제어 효율을 가진다. 하지만 지상이 제어의 중심이 되고 있기 때문에 하나의 지상시스템이 허용할 수 있는 열차 투입 대수가 제한되고 차상과 지상제어시스템 간 cyclic-path 제어흐름으로 인해 운전시격 단축에 한계를 가진다. 본 논문은 열차자율주행제어시스템을 위한 간격제어와 차상중심 분산형 연동 알고리즘을 제안한다. 열차자율주행제어시스템은 차상에서 간격제어와 함께 분기제어를 수행하므로 선로와 분기기는 공유자원인 동시에 세마포어 요소이다. 제안된 열차자율주행기반 간격제어는 지상 제어시스템의 제어명령에 의존하지 않고 열차와 열차 또는 선로변 설비와의 직접적인 무선통신을 통해 열차 간격제어를 수행한다. 제안된 연동 알고리즘은 공유자원인 선로전환기가 동시에 두 대 이상의 열차가 점유하지 못하도록 선로전환기 고유 key를 이용한 세마포어 기법을 새롭게 정의한다. 시뮬레이션을 통해 제안된 열차자율주행제어시스템의 향상된 간격제어 성능을 확인하며, 차상중심 분산형 연동알고리즘과 기존의 연동장치에서 수행하던 여러 연동논리를 비교함으로써 단순화된 연동알고리즘으로 안전한 열차제어가 가능함을 확인한다.

• 제어로봇시스템학회논문지
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• 제6권12호
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• pp.1079-1085
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• 2000

In this paper, we propose a method of cooperative control (T-cell modeling) and selection of group behavior strategy (B-cell modeling) based on immune system in distributed autonomous robotic system (DARS). An immune system is the living bodys self-protection and self-maintenance system. these features can be applied to decision making of the optimal swarm behavior in a dynamically changing environment. For applying immune system to DARS, a robot is regarded as a B-cell, each environmental condition as an antigen, a behavior strategy as an antibody, and control parameter as a T-cell, respectively. When the environmental condition (antigen) changes, a robot selects an appropriate behavior strategy (antibody). And its behavior strategy is stimulated and suppressed by other robots using communication (immune network). Finally, much stimulated strategy is adopted as a swarm behavior strategy. This control scheme is based on clonal selection and immune network hypothesis, and it is used for decision making of the optimal swarm strategy. Adaptation ability of the robot is enhanced by adding T-cell model as a control parameter in dynamic environments.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1997년도 한국자동제어학술회의논문집; 한국전력공사 서울연수원; 17-18 Oct. 1997
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• pp.124-127
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• 1997

In this paper, we propose a method of cooperative control based on immune system in distributed autonomous robotic system(DARS). Immune system is living body's self-protection and self-maintenance system. Thus these features can be applied to decision making of optimal swarm behavior in dynamically changing environment. For the purpose of applying immune system to DARS, a robot is regarded as a B lymphocyte(B cell), each environmental condition as an antigen, and a behavior strategy as an antibody respectively. The executing process of proposed method is as follows. When the environmental condition changes, a robot selects an appropriate behavior strategy. And its behavior strategy is simulated and suppressed by other robot using communication. Finally much simulated strategy is adopted as a swarm behavior strategy. This control scheme is based on clonal selection and idiotopic network hypothesis. And it is used for decision making of optimal swarm strategy.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 1994년도 추계학술대회 논문집
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• pp.701-706
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• 1994

Holonic manufacturing system is a new approachto the organization and architecture of decentralized, autonomous and cooperative manufacturing system. The new paradigm combines the concepts of hierarchical systems and the integration of autonomous elements in distributed system. Today's scheduling and control techniques are mostly based on a centralized structure. Only little work has been done on scheduling and control of decentralized, autonomous and cooperative manufacturing system. This paper proposes a new approach IPM(Interactive Prediction Method) for scheduling and control of holonic manufacturing system.

• 한국지능시스템학회논문지
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• 제11권7호
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• pp.591-597
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• 2001

In this paper, we propose a method of cooperative control (T-cell modeling) and selection of group behavior strategy (B-cell modeling) based on immune system in distributed autonomous robotic system (DARS). Immune system is living body's self-protection and self-maintenance system. These features can be applied to decision making of optimal swarm behavior in dynamically changing environment. For applying immune system to DARS, a robot is regarded as a B-cell, each environmental condition as an antigen, a behavior strategy as an antibody and control parameter as a T-cell respectively. The executing process of proposed method is as follows. When the environmental condition changes, a robot selects an appropriate behavior strategy. And its behavior strategy is stimulated and suppressed by other robot using communication. Finally much stimulated strategy is adopted as a swarm behavior strategy. This control school is based on clonal selection and idiotopic network hypothesis. And it is used for decision making of optimal swarm strategy. By T-cell modeling, adaptation ability of robot is enhanced in dynamic environments.