• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1286-1290
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• 2004

This paper proposes a Distributed Autonomous Robotic System (DARS) based on an Artificial Immune Network (AIN) and a Classifier System (CS). The behaviors of robots in the system are divided into global behaviors and local behaviors. The global behaviors are actions to search tasks in environment. These actions are composed of two types: aggregation and dispersion. AIN decides one between these two actions, which robot should select and act on in the global. The local behaviors are actions to execute searched tasks. The robots learn the cooperative actions in these behaviors by the CS in the local. The relation between global and local increases the performance of system. Also, the proposed system is more adaptive than the existing system at the viewpoint that the robots learn and adapt the changing of tasks.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.5 no.2
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• pp.151-156
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• 2005

This paper proposes a Distributed Autonomous Robotic System(DARS) based on an Artificial Immune System(AIS) and a Classifier System(CS). The behaviors of robots in the system are divided into global behaviors and local behaviors. The global behaviors are actions to search tasks in given environment. These actions are composed of two types: aggregation and dispersion. AIS decides one among these two actions, which robot should select and act on in the global. The local behaviors are actions to execute searched tasks. The robots learn the cooperative actions in these behaviors by the CS in the local one. The proposed system will be more adaptive than the existing system at the viewpoint that the robots learn and adapt the changing of tasks.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1997.10a
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• pp.357-360
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• 1997

Abstract: In teleoperation field robotic system such as hydraulically actuated robotic excavator, the maneuverability and convenience is the most important part in the operation of robotic excavator. Particularly the force information is important in dealing with digging and leveling operation in the teleoperated excavator. Excavators are also subject to a wide variation of soil-tool interaction forces. This paper presents a new force reflecting joystick in a velocity-force type bilateral teleoperation system. The master system is electrical joystick and the slave system IS hydraulically actuated cylinder with linear position sensor. Particularly Pneumatic motor is used newly in the master joystick for force reflection and the information of the pressure of salve cylinder is measured and utilized as the force feedback signal. Also force-reflection gain greatly affects the excavation performance of a hydraulically actuated robotic system and it is very difficult to determine it appropriately since slave excavator contacts with various environments such as from soft soil to rock. To overcome this, this paper proposes a force-reflection gain selecting algorithm based on artificial neural network and fuzzy logic.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.5
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• pp.435-441
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• 2013

A swarm robot system consists of with multiple mobile robots, each of which is called an agent. Each agent interacts with others and cooperates for a given task and a given environment. For the swarm robotic system, the loss of the entire work capability by malfunction or damage to a single robot is relatively small and replacement and repair of the robot is less costly. So, it is suitable to perform more complex tasks. The essential component for a swarm robotic system is an inter-robot collaboration strategy for teamwork. Recently, the swarm intelligence theory is applied to robotic system domain as a new framework of collective robotic system design. In this paper, FA (Firefly Algorithm) which is based on firefly's reaction to the lights of other fireflies and their social behavior is employed to optimize the group behavior of multiple robots. The main application of the firefly algorithm is performed on path planning of swarm mobile robots and its effectiveness is verified by simulations under various conditions.

• Journal of Power System Engineering
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• v.2 no.2
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• pp.47-54
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• 1998

Underwater robotic vehicles(URVs) have been an important tool for various underwater tasks such as pipe-lining, data collection, hydrography mapping, construction, maintenance and repairing of undersea equipment, etc because they have greater speed, endurance, depth capability, and safety than human divers. As the use of such vehicles increases, the vehicle control system is one of the most critical subsystems to increase autonomy of the vehicle. The vehicle dynamics are nonlinear and their hydrodynamic coefficients are often difficult to estimate accurately. It is desirable to have an intelligent vehicle control system because the fixed-parameter linear controller such as PID may not be able to handle these changes promptly and result in poor performance. In this paper we described and analyzed a new type of fuzzy model-based controller which is designed for underwater robotic vehicles and based on Takagi-Sugeno-Kang(TSK) fuzzy model. The proposed fuzzy controller: 1) is a nonlinear controller, but a linear state feedback controller in the consequent of each local fuzzy control rule; 2) can guarantee the stability of the closed-loop fuzzy system; 3) is relatively easy to implement. Its good performance as well as its robustness to parameter changes will be shown and compared with those of the PID controller by simulation.

• Journal of information and communication convergence engineering
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• v.8 no.5
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• pp.591-594
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• 2010

Control devices perform various works for us in many areas. The device is being utilized for precision movement of certain object. In as much as control devices are activated by means of motors, motor control is important.[1][2] Generally, servo motors capable of precision control are more frequently used than DC motors. Use of 3 motors allows 3- way movement. Medical controllers for surgical operation require high precision. [3][4][5][6] AX-12, a servo motor can realize various types of movement. AX-12 can be easily manufactured in the form of a robotic arm and has features that MCU and its peripheral circuits are simple. For precision movement, 3 motors can be controlled by use of a single joystick and 2 buttons, with movement angles being adjusted by having preset values in the program changed.[7][8] By virtue of this study, we have realized small precision robotic arm system utilizing single joystick and 2 buttons. This system can control the robotic arm in the direction desired by the user. The system has been designed such that a joystick controls 2 motors with the remaining motor being controlled by a button. Single MCU is tasked with both control and movement.[9] We have shown precision robotic arm system in the Figure contained in the conclusion part and made reference to results of analysis in there. It has also been demonstrated that the system can be utilized in the industry.[8]

• Journal of information and communication convergence engineering
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• v.9 no.6
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• pp.743-746
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• 2011

An implementation for surface EMG network analysis and vertical control system of robotic arm is presented in this paper. The transmembranes are simulated by equivalent circuit and cable equation for propagation to be converted to circuit networks. The implementation is realized to be derived from the detecting EMG signal from 3 electrodes, and EMG transmembrane signals of human arm muscles are detected by several surface electrodes, high performance amplifier and filtering, converting analog to digital data and driving a servomotor for spontaneous robotic arm. The system is experimented by monitoring multiple steps vertical control angles corresponding to biceps muscle movement. The experimental results are that the vertical moving control level is measured to around 2 degrees and mean error ranges are lower 5%.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.29 no.4 s.235
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• pp.540-554
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• 2005

This paper presents a motion planning and control method for the dexterous manipulation with a robotic hand. For a given trajectory of an object, a simulation system calculates the necessary joint displacements and contact forces at the fingertip surfaces. These joint displacements and contact forces are the reference inputs to the control loops of the robotic fingers. A task is decomposed into a set of primitive motions, and each primitive motion is executed using the planned output of the simulation system as the reference. Force sensors and dynamic tactile sensors are used to adapt to errors and uncertainties encountered during manipulation. Several experimental results are presented.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.10a
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• pp.131-134
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• 2005

This paper presents a computer-aided simulation and robotic-assisted execution technology of external fixation method to achieve fracture reduction and deformity correction in long bones. Combining the kinematic analysis with a graphic model of the tibia and the fixator allowed 3D simulation and visualization of the adjustments required to reduce fracture or correct bone deformity as a pre-operative planning tool. The developed robot model provided accurate deformity correction with small residual deformity based on the results of the planning. By incorporating the robot model with image-guided system and computer-aided planning, the integrated system could be useful for computer-aided pre-operative planning and robotic-assisted execution in fracture treatment and bone deformity surgery.

• Korean Journal of Computational Design and Engineering
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• v.16 no.6
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• pp.437-448
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• 2011

A robotic spatial augmented reality (RSAR) system combines a robotics technology with a spatial augmented reality system (SAR) where cameras are used to recognize real objects and projectors augment information and user interface directly on the surface of the recognized objects, rather than relying on handheld display devices. Moreover, a robotic module is actively used to discover and utilize the context of users and environments. The control of a RSAR system involves several issues from different technical fields such as classical inverse kinematics of motors where projector-camera pairs are mounted, inverse projection problems to find appropriate internal/external parameters of projectors and cameras, and image warping in graphics pipeline to compensate the kinematic constraints. In this paper, we investigate various control issues related to a RSAR system and propose basic approaches to handle them, specially focused on the prototype RSAR system developed in ETRI.