• Journal of Institute of Control, Robotics and Systems
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• v.21 no.2
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• pp.150-156
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• 2015

In this paper, a marionette control system using wrist and finger gestures through an IMU sensor is studied. The signals from the sensor device are conditioned and recognized, then the commands are sent to the 8 motors of the marionette via Bluetooth (5 motors control the motion of the marionette, and 3 motors control the location of the marionette). It is revealed that the degree of freedom of fingers are not independent from each other, therefore, some gestures are hardly made. Gesture mode changes for difficult postures of the fingers in cases of a lack of finger DOF are proposed. Therefore, the gesture mode change switches the assignment of gesture as required. Experimental results show that gesture mode change is successful for appropriate postures of a marionette.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.21 no.3
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• pp.361-368
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• 1997

In order to eliminate position errors existing at the steady state in the motion control of robotic manipulators, a new fuzzy control algorithm is propeosed using three variables, position error, velocity error and integral of position errors as input variables of the fuzzy controller. Although the number of input variables of the fuzzy controller is increased from two to three, the number of fuzzy control rules is just increased by two. Three dimensional look-up table is used to reduce the computational time in real-time control, and a technique reducing the amount of necessary memory is introduced. Simulation and experimental studies show that the position errors at the steady state are decreased more than 90% compared to those of existing fuzzy controller when the proposed fuzzy controller is applied to the 2 axis direct drive SCARA robot manipulator.

• Journal of Institute of Control, Robotics and Systems
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• v.5 no.7
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• pp.841-847
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• 1999

For successful assembly of flexible parts, informations about their deformation as well as possible misalignments between the holes and their mating parts are essential. Such informations can be acquired from visual sensors. For robotic assembly, the corrective assembly motion to compensate for such misalignments has to be determined from the measured informations. However, this may not be simply derived from the measured misalignment alone because the part deformation progressively occurs during misalignment compensation. Based on the analysis of flexible parts assembly process, this paper presents a neural net-based inference system that can infer the complex relationship between the corrective motion and the measured information of parts deformation and misalignments. And it verifies the performance of the implemented inference system. The results show that the proposed neural net-based misalignment compensation algorithm Is effective in compensating for the lateral misalignment, and that it can be extended to the assembly tasks under more general conditions.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.24.4-24
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• 2001

Many livings form groups which we consider as collective systems. The collective motion of the group shows various dynamics and patterns, and many model equations are proposed to explain such phenomenon. In our previous work, We proposed simple deterministic model which shows various types of group behaviors. In this paper, we modify it in order to apply to a real robotic system. Here we assume that the space resolution of each robot´s sensors is low and that the sensors detect the nearest robots. It was confirmed the robots with modified model also shows various types of motion.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.2
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• pp.103-109
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• 2012

Fish generates large thrust through an oscillating motion with a compliant joint of caudal fin. The compliance of caudal fin affects the thrust generated by the fish. Due to the flexibility of the fish, the fish can generate a travelling wave motion which is known to increase the efficiency of the fish. However, a detailed research on the relationship between the flexible joint and the thrust generation is needed. In this paper, the compliant joint of a caudal fin is implemented in the driving mechanism of a robotic fish. By varying the driving frequency and stiffness of the compliant joint, the relationship between the thrust generation and the stiffness of the flexible joint is investigated. In general, as the frequency increases, the thrust increases. When higher driving frequency is applied, higher stiffness of the flexible joint is needed to maximize the thrust. The bending angles between the compliant joint and the caudal fin are compared with the changes of the thrust in one cycle. This result can be used to design the robotic fish which can be operated at the maximum thrust condition using the appropriate stiffness of the compliant joint.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2004.10a
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• pp.1327-1330
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• 2004

An underwater robotic system has been developed and applied to visual inspection of reactor vessel internals. The Korea Electric Power Robot for Visual Test (KeproVt) consists of an underwater robot, a vision processor-based measuring unit, a master control station and a servo control station. The robot guided by the control station with the measuring unit can be controlled to have any motion at any position in the reactor vessel with $\pm$1 cm positioning and $\pm$2 degrees heading accuracies with enough precision to inspect reactor internals. A simple and fast installation process is emphasized in the developed system. The developed robotic system was successfully deployed at the Younggwang Nuclear Unit 1 for the visual inspection of reactor internals.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.65-68
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• 1996

Robotic manipulators have become increasingly important in the field of flexible automation. High speed and high-precision trajectory tracking are indispensable capabilities for their versatile application. The need to meet demanding control requirement in increasingly complex dynamical control systems under significant uncertainties, leads toward design of intelligent manipulation robots. This paper presents a new approach to the design of neural control system using digital signal processors in order to improve the precision and robustness. The TMS32OC31 is used in implementing real time neural control to provide an enhanced motion control for robotic manipulators. In this control scheme, the networks introduced are neural nets with dynamic neurons, whose dynamics are distributed over all the, network nodes. The nets are trained by the distributed dynamic back propagation algorithm. The proposed neural network control scheme is simple in structure, fast in computation, and suitable for implementation of real-time, control. Performance of the neural controller is illustrated by simulation and experimental results for a SCARA robot.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10a
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• pp.1144-1148
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• 1991

The problems occurred when developing a automatic wheel deburring system are to make effective flexibility in model change and the irregularity of the position/shape of the burr, to select optimal robotic manufacturing process and to develope optimal end effector. The locations where burr exists are on flange, rim and spoke. Here will be discussed the optimal solution for the removal of rim burr by using robot. The research can be summarized as the automatic robot path generation by recognizing rim contour and automatic deburring process technique. Various rim contour data is generated automatically when the sensor which is fixed to robot is moving with the parallel motion to the wheel center axis and this generated data is transferred to the data storage system and converted to the robot path data. The robotic tool system which is suitable to the rim deburring process is developed by integrating tool, compliance function and sensor. And factory automation system controlled by robot controller and PC is developed. This system shows good productivity and flexibility.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1997.04a
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• pp.761-765
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• 1997

Our study of rider's postulator stability and tracking control on a unicycle began form the observation of a human riding. The system including unicycle and human operationg his unicycle is a fuzzy intelligent biomechanical model on basis of instinct and intuition search mechanisms. We proposed a robotic unicycle with one wheel and one body as a basic mode and derived equation of motion to this model. Our works is in making out fuzzy look-up table to control robotic unicycle. Fuzzy look-up table were determined for staight line and curve under reasonable inference emulating human's instinct and intuition riding a unicyale. Simulation results show that postulator stability and tracking control on both straight line and curve were successful by using proposed each fuzzy look-up table.

• ETRI Journal
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• v.45 no.3
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• pp.479-491
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• 2023

The automation of agricultural machines is an irreversible trend considering the demand for improved productivity and lack of labor in handling agricultural tasks. Unstructured working environments and weather often inhibit a seemingly simple task from being fully autonomously performed. In this context, we propose a remote driving system (RDS) to aid agricultural machines designed to operate autonomously. Particularly, we modify a commercial speed sprayer for orchard environments into a robotic speed sprayer to evaluate the proposed RDS's usability and test three sensor configurations in terms of human performance. Furthermore, we propose a confidence error ellipsebased task performance measure to evaluate human performance. In addition, we present field experimental results describing how the sensor configurations affect human performance. We find that a combination of a semiautonomous line tracking device and a wide-angle camera is the most effective for spraying. Finally, we discuss how to improve the proposed RDS in terms of usability and obtain a more accurate measure of human performance.