• The Journal of Korea Robotics Society
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• v.8 no.1
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• pp.1-7
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• 2013

Body gesture Recognition has been one of the interested research field for Human-Robot Interaction(HRI). Most of the conventional body gesture recognition algorithms used Hidden Markov Model(HMM) for modeling gestures which have spatio-temporal variabilities. However, HMM-based algorithms have difficulties excluding meaningless gestures. Besides, it is necessary for conventional body gesture recognition algorithms to perform gesture segmentation first, then sends the extracted gesture to the HMM for gesture recognition. This separated system causes time delay between two continuing gestures to be recognized, and it makes the system inappropriate for continuous gesture recognition. To overcome these two limitations, this paper suggests primitive body model encoding, which performs spatio/temporal quantization of motions from human body model and encodes them into predefined primitive codes for each link of a body model, and Selective/Asynchronous Input-Parallel State machine(SAI-PSM) for multiple-simultaneous gesture recognition. The experimental results showed that the proposed gesture recognition system using primitive body model encoding and SAI-PSM can exclude meaningless gestures well from the continuous body model data, while performing multiple-simultaneous gesture recognition without losing recognition rates compared to the previous HMM-based work.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.29B no.11
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• pp.120-129
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• 1992

In this paper we propose a fuzzy-neural network(FNN) which includes both advantages of the fuzzy logic and the neural network. The basic idea of the FNN is to realize the fuzzy rule-base and the process of reasoning by neural network and to make the corresponding parameters be expressed by the connection weights of neural network. After constructing the FNN, a novel controller consisting of a conventional P-controller and a FNN is explained. In this control scheme, the rule-base of a FNN are automatically generated by error back-propagation algorithm. Also the parallel connection of the P-controller and the FNN can guarantee the stability of a plant at initial stage before the rules are completely created. Finally the effectiveness of the proposed strategy will be verified by computer simulations using a 2 degree of freedom robot manipulator.

• Journal of the Korean Society for Precision Engineering
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• v.33 no.7
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• pp.579-586
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• 2016

This paper describes kinematic analysis of a 6-degrees-of-freedom (DOF) ultra-precision positioning stage based on a flexure hinge. The stage is designed for processes which require ultra-precision and high load capacities, e.g. wafer-level precision bonding/assembly. During the initial design process, inverse and forward kinematic analyses were performed to actuate the precision positioning stage and to calculate workspace. A two-step procedure was used for inverse kinematic analysis. The first step involved calculating the amount of actuation of the horizontal actuation units. The second step involved calculating the amount of actuation of the vertical actuation unit, given the the results of the first step, by including a lever hinge mechanism adopted for motion amplification. Forward kinematic analysis was performed by defining six distance relationships between hinge positions for in-plane and out-of-plane motion. Finally, the result of a circular path actuation test with respect to the x-y, y-z, and x-z planes is presented.

• Journal of Sensor Science and Technology
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• v.8 no.1
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• pp.80-88
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• 1999

This paper deals with the position determination problem of stereo camera systems used as a sensor for 3D robotic manipulation. Stereo cameras having parallel rays of sight and been set up on the same baseline are assumed. The distance between the sensor and the space measured is determined so as to get insensitive parameters to the uncertainty of control points used for calibration and to satisfy the error condition set by considering the repeatability of the robot. The baseline width is determined by minimizing the mutual effect of 3D positional error and stereo image coordinate error. Unlike existing techniques, the technique proposed here is developed without complicated constraints and modelling process of the object to be observed. Thus, the technique of this paper is more general and its effectiveness is proved by simulation.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.27 no.1
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• pp.18-25
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• 2003

A haptic hand controller (HHC) operated by the user’s hand can receive information on position and orientation of the hand and display force and moment generated in the virtual environment to the hand. In this paper, a 3-DOF hand controller is first presented, in which all the actuators are mounted on the fixed base by combining a 5-bar linkage and a gimbal mechanism. The 6-DOF HHC is then designed by connecting these two 3-DOF devices through a handle which consists of a screw and nut. Analysis using performance index is carried out to determine the dimensions of the device. The HHC control system consists of the high-level controller for kinematic and static analysis and the low-level controller for position sensing and motor control. The HHC used as a user interface to control the mobile robot in the virtual environment is given as a simple application.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.21 no.10
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• pp.1551-1560
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• 1997

This study is devoted to the detection of the 3-dimensional point obstacles on the plane by using accumulated scan line images. The proposed accumulating only one scan line allow to process image at real time. And the change of motion of the feature in image is small because of the short time between image frames, so it does not take much time to track features. To obtain recursive optimal obstacles position and robot motion along to the motion of camera, Kalman filter algorithm is used. After using Kalman filter in case of the fixed environment, 3-dimensional obstacles point map is obtained. The position and motion of moving obstacles can also be obtained by pre-segmentation. Finally, to solve the stereo ambiguity problem from multiple matches, the camera motion is actively used to discard mis-matched features. To get relative distance of obstacles from camera, parallel stereo camera setup is used. In order to evaluate the proposed algorithm, experiments are carried out by a small test vehicle.

• Journal of the Korean Society for Precision Engineering
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• v.32 no.3
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• pp.263-268
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• 2015

This paper describes lost motion analysis for a novel 6-DOF ultra-precision positioning stage. In the case of flexure hinge based precision positioning stage, lost motion is generated when the displacement of actuator is not delivered completely to the end-effector because of the elasticity of flexure hinge. Consequently, it is need to compute amount of lost motion to compensate the motion or to decide appropriate control method for precision positioning. Lost motion analysis for the vertical actuation unit is presented. The analysis results are presented in two ways: analytic and numerical analyses. It is found that they closely coincide with each other by 1% error. In finite element analysis result, the amount of lost motion is turned out to be about 3%. Although, the amount is not so large, it is necessary procedure to check the lost motion to establish the control method.

• Proceedings of the KSME Conference
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• 2008.11a
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• pp.768-772
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• 2008

Various scanning systems have been studied in many industrial areas to acquire a range data or to reconstruct an explicit 3D model. Currently optical technology has been used widely by virtue of noncontactness and high-accuracy. In this paper, we describe a 3D laser scanning system developped to reconstruct the 3D surface of a large-scale object such as a curved-plate of ship-hull. Our scanning system comprises of 4ch-parallel laser vision modules using a triangulation technique. For multi laser vision, calibration method based on least square technique is applied. In global scanning, an effective method without solving difficulty of matching problem among the scanning results of each camera is presented. Also minimal image processing algorithm and robot-based calibration technique are applied. A prototype had been implemented for testing.

• Proceedings of the KIPE Conference
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• 2002.07a
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• pp.711-714
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• 2002

Thermal infrared camera have poor image qualities compared to commercial CCD cameras, as in contrast, brightness, and. resolution. To compensate the poor Image quality problems associated with the thermal infrared camera, the technique of superimposing thermal infrared image into real ccd image is proposed. The mobile robot KAEROT/m2, loaded with sensor head system at the mast, is entered to monitor leakage of heavy water and thermal abnormality of the calandria reactor area in overhaul period. The sensor head system is composed of thermal infrared camera and cod camera In parallel. When thermal abnormality on observation points and areas of calandria reactor area is occurred, unusual hot image taken from thermal infrared camera is superimposed on real CCD image. In this inspection experiment, more accurate positions of thermal abnormalities on calandria reactor area can be estimated by using technique of mapping thermal infrared image into CCD image, which include characters arranged in MPOQ order.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.54 no.3
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• pp.156-165
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• 2005

Human being recognizes the physical world by integrating a great variety of sensory inputs, the information acquired by their own action, and their knowledge of the world using hierarchically parallel-distributed mechanism. In this paper, authors propose the sensor fusion system that can recognize multiple 3D objects from 2D projection images and tactile informations. The proposed system focuses on improving recognition performance of 3D objects. Unlike the conventional object recognition system that uses image sensor alone, the proposed method uses tactual sensors in addition to visual sensor. Neural network is used to fuse the two sensory signals. Tactual signals are obtained from the reaction force of the pressure sensors at the fingertips when unknown objects are grasped by four-fingered robot hand. The experiment evaluates the recognition rate and the number of learning iterations of various objects. The merits of the proposed systems are not only the high performance of the learning ability but also the reliability of the system with tactual information for recognizing various objects even though the visual sensory signals get defects. The experimental results show that the proposed system can improve recognition rate and reduce teeming time. These results verify the effectiveness of the proposed sensor fusion system as recognition scheme for 3D objects.