• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.2126-2131
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• 2005

Interactions of a humanoid with a human are important, when the humanoid is requested to provide people with human-friendly services in unknown or uncertain environment. Such interactions may require more complicated and human-like behaviors from the humanoid. In this work the arm motions of a human are discussed as the early stage of human motion imitation by a humanoid. A motion capture system is used to obtain human-friendly arm motions as references. However the captured motions may not be applied directly to the humanoid, since the differences in geometric or dynamics aspects as length, mass, degrees of freedom, and kinematics and dynamics capabilities exist between the humanoid and the human. To overcome this difficulty a method to adapt captured motions to a humanoid is developed. The geometric difference in the arm length is resolved by scaling the arm length of the humanoid with a constant. Using the scaled geometry of the humanoid the imitation of actor's arm motions is achieved by solving an inverse kinematics problem formulated using optimization. The errors between the captured trajectories of actor arms and the approximated trajectories of humanoid arms are minimized. Such dynamics capabilities of the joint motors as limits of joint position, velocity and acceleration are also imposed on the optimization problem. Two motions of one hand waiving and performing a statement in sign language are imitated by a humanoid through dynamics simulation.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.1
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• pp.46-51
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• 2007

This paper is to present gesture analysis for human-robot interaction. Understanding human emotions through gesture is one of the necessary skills fo the computers to interact intelligently with their human counterparts. Gesture analysis is consisted of several processes such as detecting of hand, extracting feature, and recognizing emotions. For efficient operation we used recognizing a gesture with HMM(Hidden Markov Model). We constructed a large gesture database, with which we verified our method. As a result, our method is successfully included and operated in a mobile system.

• Journal of Korean Society of Water and Wastewater
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• v.29 no.6
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• pp.693-702
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• 2015

The objective of this study is to investigate and evaluate that a roadside tree root intrudes sewer network systems. Two approaches were performed to assess the characteristics of tree root intrusion. First, the characteristics of tree roots that had invaded sewers were directly observed by means of closed-circuit television inspection robot. Second, the intrusion proportions of tree root into rain gutters in the sampling area were investigated. As tree species of low intrusion proportions, the results indicated that Ginkgo biloba Linn. and Acer buergerianum Miq. were 1.7% and 4.3%. On the other hand, tree species of high intrusion proportions were Metasequoia glyptostroboides Hu et Cheng, Ulmus davidiana var. japonica Nakai and Zelkova serrata Makino as 22.2%, 20.4%, and 17.6% respectively. In particular, sewers and gutters around Zelkova species should be the focus of maintenance work because of the high proportion of these trees on roadsides.

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.7
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• pp.870-874
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• 2005

This paper presents capacitive tactile sensor that can detect normal and shear forces. This tactile sensor consists of index plate, sensing plate, and elastic dielectric layer. The calculated sensing character is based on the changes of space between two horizontal plate. Larger overlap areas and narrow space between top and bottom plate guarantees higher sensitivity. Tactile sense information can be calculated from the changes of phase of output signal. The symmetric arrangement of sensing plates makes the manufacturing process easier and guarantees the stability of the structure. In this paper, the sensor structure is designed, the mechanism of the Proposed sensor is theoretically explained, and the simulated result is presented.

• Journal of the Korean Association of Oral and Maxillofacial Surgeons
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• v.40 no.1
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• pp.27-31
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• 2014

Various surgical techniques, such as endoscopic surgery and robotic surgery, are developed to optimize the esthetic outcome even in operations for malignancy. A modified face-lift or retroauricular approach are used to minimize postoperative scarring. Recently, robot-assisted surgery is being done in various fields and considered as favorable treatment method by many surgeons. However its high cost is a nonnegligible fraction for many patients. On the other hand, endoscopic surgery, which is cheaper than robotic surgery, is minimally invasive with contentable neck dissection. Although it is a difficult technique for a beginner surgeon due to its limited operation view, we suppose it as an alternative method for robotic surgery. Herein, we report two cases of endoscopic neck dissection via retroauricular incision with a discussion regarding the pros and cons of endoscopic neck dissection.

• 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.

• The Journal of Korea Robotics Society
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• v.15 no.3
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• pp.240-247
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• 2020

This paper presents a novel knitted data glove system for pattern classification of hand posture. Several experiments were conducted to confirm the performance of the knitted data glove. To find better sensor materials, the knitted data glove was fabricated with stainless-steel yarn and silver-plated yarn as representative conductive yarns, respectively. The result showed that the signal of the knitted data glove made of silver-plated yarn was more stable than that of stainless-steel yarn according as the measurement distance becomes longer. Also, the pattern classification was conducted for the performance verification of the data glove knitted using the silver-plated yarn. The average classification reached at 100% except for the pointing finger posture, and the overall classification accuracy of the knitted data glove was 98.3%. With these results, we expect that the knitted data glove is applied to various robot fields including the human-machine interface.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.11
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• pp.895-903
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• 2016

In a fire disaster in a tunnel, people should be rescued immediately using the information obtained from cameras or sensors. However, in heavy smoke from a fire, people cannot be clearly identified by a mounted CCTV, which is only effective in a clear environment. A thermal camera can be an alternative to this in smoky situations and is capable of detecting people from their emitted thermal energy. On the other hand, the thermal image camera has a smaller field of view than an ordinary camera due to its lens characteristics and temperature error, etc. In order to cover a relatively wide area, panoramic image construction needs to be implemented. In this work, a template-based similarity matching algorithm for constructing the panorama image is proposed and its performance is verified through experiments. This scheme provides guidelines for coping with difficulty in image construction, which requires an exact correspondence search for two images in cases of heavy smoke.

• Transactions on Control, Automation and Systems Engineering
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• v.3 no.1
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• pp.66-70
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• 2001

This paper describes the design of a two-axis force sensor for robots finger. In detects the x-direction force Fx and y-direction force Fy simultaneously. In order to safely grasp an unknown object using the robots fingers, they should detect the force or gripping direction and the force of gravity direction, and perform the force control using the forces detected. Therefore, the robots hand should be made by the robots finger with tow-axis force sensor that can detect the x-direction force and y-direction force si-multaneously. Thus, in this paper, the two-axis force sensor for robots finger is designed using several parallel-plate beams. The equations to calculate the strain of the beams according to the force in order to design the sensing element of the force sensor are derived and these equations are used to design the aize of two-axis force sensor sensing element. The reliability of the derive equa-tions is verified buy performing a finite element analysis of the sensing element. The strain obtained through this process is compared to that obtained through the theory analysis and a characteristics test of the fabricated sensor. It reveals that the rated strains calculated from the derive equations make a good agreement with the results from the Finite Element Method analysis and from the character-istic test.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.53 no.2
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• pp.127-134
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• 2004

In this paper, human motor behaving model based sensory motor coordination(SMC) algorithm is implemented on robotic grasping task. Compare to conventional SMC models which connect sensor to motor directly, the proposed method used biologically inspired human behaving system in conjunction with SMC algorithm for fast grasping force control of robot arm. To characterize various grasping objects, pressure sensors on hand gripper were used. Measured sensory data are simultaneously transferred to perceptual mechanism(PM) and long term memory(LTM), and then the sensory information is forwarded to the fastest channel among several information-processing flows in human motor system. In this model, two motor learning routes are proposed. One of the route uses PM and the other uses short term memory(STM) and LTM structure. Through motor learning procedure, successful information is transferred from STM to LTM. Also, LTM data are used for next moor plan as reference information. STM is designed to single layered perception neural network to generate fast motor plan and receive required data which comes from LTM. Experimental results showed that proposed method can control of the grasping force adaptable to various shapes and types of greasing objects, and also it showed quicker grasping-behavior lumining time compare to simple feedback system.