• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.2880-2882
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• 2000

In the case of designing autonomous robot architecture using deliberative and reactive control methods, we can use mixed hybrid form as well as purely reactive scheme or purely deliberative scheme respectively according to its own goal and environment within the robot operates, It needs time and endeavors to design robot control architecture in either case above. In our research, we implemented a 3-dimensional robot simulator in order to help designing reactive/deliberative autonomous robot control architecture by offering methods which is capable of selecting design parameters and confirming its performances. It can be used, of course, to design purely reactive or purely deliberative architecture. The architecture and performance of simulator is shown and a sample hybrid robot architecture designed with the simulator is introduced in this article.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.2342-2345
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• 2005

Robot control system considers various requirements. Firstly, it needs adaptation for unpredictable and dynamic environment. Secondly, it needs way to make do not injurious action to human because live with a person. Thirdly, it needs processing about aim of robots. In this paper proposed that these requirements effective robot control architecture. Robot control architecture can divide Deliberative, Reactive, Hybrid. Recently, robot control architecture that come Deliberative and use hybrid architecture that apply advantage of Reactive architecture is studied much. Hybrid control purpose to combine the real-time response of Reactive with the rationality of Deliberative. Our purpose is enhancement of hybrid architecture that is studied in these days. Proposed architecture that applied human's nervous system can reduce relativity between each module of existent architecture and drive response speed guarantee and safe robot action.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.14 no.5
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• pp.27-34
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• 2005

To accomplish various and complex tasks by intelligent robots, improvement is needed not only in mechanical system architecture but also in control system architecture. Hybrid control architecture has been suggested as a mutually complementing architecture of the weak points of a deliberative and a reactive control. This paper addresses a control architecture of robots, and a behavior representation methodology. The suggested control architecture consists of three layers of deliberative, sequencing, and reactive as hybrid control architecture. Multi-layer behavior model is employed to represent desired tasks. 3D simulation will be conducted to verify the applicability of suggested control architecture and behavior representation method.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1178-1183
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• 2003

As personal robots coexist with a person with a role to help a person, while adapting various human life and environment, the personal robots have to accommodate frequently-changing or different-from-home-to-home environment. In addition, personal robots may have many kinds of different Kinematic configurations depending on the capabilities. Some may have a mobile base and others may have arms and a head. The motivation of this study arises from this not-well-defined home environment and varying Kinematic configuration. So the goal of this study is to develop a general control architecture for personal robots. There exist three major architectures; deliberative, reactive and hybrid. We found that these are applicable only for the defined environment with a fixed Kinematic configuration. Neither could accommodate the above two requirements. For the general solution, we propose a Supervised Hybrid Architecture (SHA), in which we use double layers of deliberative and reactive controls, distributed control with a modular design of Kinematic configurations, and real-time Linux OS. Deliberative and reactive actions interact through a corresponding arbitrator. These arbitrators help a robot to choose an appropriate architecture depending on the current situation to successfully perform a given task. The distributed control modules communicate through IEEE 1394 for the easy expandability. With a personal robot platform with a mobile base, two arms, a head and a pan-tilt stereo eye system, we tested the developed SHA for static as well as dynamic environments. For this application, we developed decision-making rules for selecting appropriate control methods for several situations of navigation task. Examples are shown to show the effectiveness.

• Journal of Institute of Control, Robotics and Systems
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• v.12 no.2
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• pp.154-160
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• 2006

Instantaneous reaction and intelligence are required for autonomous mobile robots to achieve multiple goals in the unpredictable and dynamic environments. Design of the appropriate control architecture and clear definitions of systems are needed to construct and control these robots. This research proposes the hybrid deliberative/reactive control architecture which consists of three layers and uses the method of software structure design. The highest layer, Deliberative Layer makes the overall run-time schedule for navigation and/or manipulation, and the middle layer, Task Execution Layer carries out various missions. The lowest layer, Reactive Layer enables a robot to react rapidly in the dynamic environment and controls the mechanical devices concurrently. This paper proposes independent system supervisors called Manager to reuse the modules so that the Manager supports common use of the system and multi-processing tasks. It is shown that the mobile robot based on the proposed control scheme can perform the basic navigation and cope with the dynamic obstacles reasonably well.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.10a
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• pp.984-988
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• 2005

To accomplish various and complex tasks by intelligent robots, improvement is needed not only in mechanical system architecture but also in control system architecture. Hybrid control architecture has been suggested as a mutually complementing architecture of the weak points of a deliberative and a reactive control. This paper addresses a control architecture of robots, and a behavior representation methodology. The suggested control architecture consists of three layers of deliberative, sequencing, and reactive as hybrid control architecture. Multi-layer behavior model is employed to represent desired tasks. 3D simulation will be conducted to verify the applicability of suggested control architecture and behavior representation method.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.6
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• pp.510-517
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• 2005

In this paper, an open architecture control system for automated container cranes is investigated. The hardware architecture for automating cranes is first discussed. A standard reference model for cranes based upon the OSACA platform is proposed, in which three modules are suggested: hardware module, operating system module, and application software module. Finally, a hybrid control system combining deliberative and reactive controls for autonomous operations of the cranes is implemented.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1039-1043
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• 2005

Despite the many significant advances made in robot architecture, the basic approaches are deliberative and reactive methods. They are quite different in recognizing outer environment and inner operating mechanism. For this reason, they have almost opposite characteristics. Later, researchers integrate these two approaches into hybrid architecture. In such architecture, Reactive module also called low-level motion control module have advantage in real-time reacting and sensing outer environment; Deliberative module also called high-level task planning module is good at planning task using world knowledge, reasoning and intelligent computing. This paper presents a framework of the integrated planning and control for mobile robot navigation. Unlike the existing hybrid architecture, it learns topological map from the world map by using MST (Minimum Spanning Tree)-based SOFM (Self-Organizing Feature Map) algorithm. High-level planning module plans simple tasks to low-level control module and low-level control module feedbacks the environment information to high-level planning module. This method allows for a tight integration between high-level and low-level modules, which provide real-time performance and strong adaptability and reactivity to outer environment and its unforeseen changes. This proposed framework is verified by simulation.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2004.04a
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• pp.465-470
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• 2004

In this paper, an open architecture control system for automatic container cranes is investigated. A standard reference model for cranes, which consists of three modules； hardware module, operating system module, and application software module, is proposed. A hybrid control architecture combining deliberative and reactive controls for the autonomous operation of the cranes is proposed. The main contributions of this paper are as follows： First, a new reference platform for the crane control system is proposed. Second, by analyzing the structure of a container crane, implementation strategies for the automatic container crane are described.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2001.04a
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• pp.540-544
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• 2001

This paper addresses a hybrid control architecture for the hospital service robot, SmartHelper. In hybrid architecture, the deliberation takes place at planning layer while the reaction is dealt through the parallel execution of operations. Hence, the system presents both a hierarchical and an heterarchical decomposition, being able to show a predictable response while keeping rapid reactivity to the dynamic environment. The deliberative controller accomplishes four functions which are path generation, selection of navigation way, command and monitoring. The reactive controller uses fuzzy and potential field method for robot navigation. Through simulation under a virtual environment IGRIP, the effectiveness of the hybrid architecture is verified.