• Journal of the Korean Association of Geographic Information Studies
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• v.19 no.4
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• pp.186-198
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• 2016

HPAI(Highly Pathogenic Avian Influenza) is a contagious animal disease that spreads rapidly by diffusion after the first occurrence. The disease has brought tremendous social costs and economic losses. KAHIS (Korea Animal Health Information System) is the integrated system for supporting the task of preventing epidemics. They provide decision-support information, recording vehicle visiting times and facility location, etc., which is possible by enforcing registration of all livestock related facilities and vehicles. KAHIS has accumulated spatial and temporal information that enables effective tracing of potential disease trajectories and diffusion through vehicle movements. The contact network is created utilizing spatial and temporal information in KAHIS to inform facility connection via vehicle visitation. Based on the contact network, it is possible to infer spatial and temporal mechanism of disease spread and diffusion. The study objective is to empirically demonstrate how to utilize primary spatial and temporal information in KAHIS in the form of the contact network. Based on the contact network, facilities with the possibility of infection can be pinpointed within the potential spatial and temporal extent where the disease has spread and diffused. This aids the decision-making process in the task of preventing epidemics. By interpreting our demonstration results, policy implications were presented. Finally, some suggestions were made to comprehensively utilize the contact network to draw enhanced decision-support information.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.37 no.8
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• pp.570-578
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• 1988

In order for a robot to carry out a precise assembly task with compliant motion, a force/torque sensor is needed. The output of the cross-bar structured force / torque sensor which is used in a peg-in-hole insertion task and attached to a SCARA type robot, is analzed. First, the relationship between the sensor outputs and the force / torque components obtained by the outputs is investigated. Second, in a peg-in-hole insertion task, the sensor outputs changing with the contact position of the peg and the hole, are analyzed. Also, the relative position of the peg and the hole is obtained from the sensor outputs. The peg-in-hole insertion task is successfully executed, using a SCARA type robot with a wrist force / torque sensor manufactured in our laboratory and the compliance algorithm from the results of this paper.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.134.4-134
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• 2001

Hydraulically driven manipulators are superior to electrically driven ones in the power density and electrical insulation. But an electro-hydraulic manipulator using hydraulic actuators has many nonlinear elements, and its parameter fluctuations are greater than those of electrically driven manipulator. So it is relatively difficult to realize not only stable contact work but also accurate force control for the autonomous field tasks such as the maintenance task of high voltage active electric line or the automatic excavation task by hydraulic excavator. In this report, we propose robust force control algorithm, which can be applied to the real field task such as the construction field, nuclear plant and so on. Proposed force controller has the same structure as that of disturbance observer for position control. The difference between force and position disturbance ...

• Science of Emotion and Sensibility
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• v.20 no.1
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• pp.67-74
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• 2017

The goal of this study is to present quantification method for empathy. The micro-movement technology (non-contact sensing method) was used to identify empathy level. Participants were first divided into two groups: Empathized and not empathized. Then, the upper body data of participants were collected utilizing web-cam when participants carried expression tasks. The data were analyzed and categorized into 0.5 Hz, 1 Hz, 3 Hz, 5 Hz, 15 Hz. The average movement, variation, and synchronization of the movement were then compared. The results showed a low average movement and variation in a group who empathized. Also, the participants, who empathized, synchronized their movement during the task. This indicates that the people concentrates with each other when empathy has been established and show different levels of movement. These findings suggest the possibility of empathy quantification using non-contact sensing method.

• Journal of the Korea Convergence Society
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• v.8 no.6
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• pp.163-170
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• 2017

In this paper want to recognize competition and cooperation as a non-contact sensing method among the social emotion that are caused by interaction. Experiments were conducted in a pattern matching task divided into competition and cooperation situations. Data collection was performed by extracting the micro-movement data of 15Hz component from the upper body image. We compared and analyzed the amount and the variation and synchronization. As a result, Amount and variation are bigger in competition than cooperation. Synchronization was higher in cooperation than competition. This can be seen as the difference between two people trying to win when they are in competition and trying to breathe each other in cooperation. This study is significant in confirming the possibility of competition and cooperation through non contact sensing method based on physiological response.

• Transactions on Control, Automation and Systems Engineering
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• v.4 no.1
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• pp.100-107
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• 2002

The advanced bilateral control algorithm, which can enlarge a reflected force by combining force reflection and compliance control, greatly enhances workability in teleoperation. In this scheme the maximum boundaries of a compliance controller and a force reflection gain guaranteeing stability and good task performance greatly depend upon characteristics of a slave arm, a master arm, and an environment. These characteristics, however, are generally unknown in teleoperation. It is, therefore, very difficult to determine such maximum boundary of the gain. The paper presented a novel method for design of an advanced bilateral controller. The factors affecting task performance and stability in the advanced bilateral controller were analyzed and a design guideline was presented. The neurofuzzy compliance model (NFCM)-based bilateral control proposed herein is an algorithm designed to automatically determine the suitable compliance for a given task or environment. The NFCM, composed of a fuzzy logic controller (FLC) and a rule-learning mechanism, is used as a compliance controller. The FLC generates compliant motions according to contact forces. The rule-learning mechanism, which is based upon the reinforcement learning algorithm, trains the rule-base of the FLC until the given task is done successfully. Since the scheme allows the use of large force reflection gain, it can assure good task performance. Moreover, the scheme does not require any priori knowledge on a slave arm dynamics, a slave arm controller and an environment, and thus, it can be easily applied to the control of any telerobot systems. Through a series of experiments effectiveness of the proposed algorithm has been verified.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.05a
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• pp.419-421
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• 2018

Cloud vehicular networks are a promising paradigm to improve vehicular through distributing computation tasks between remote clouds and local vehicular terminals. Software-Defined Network(SDN) can bring advantages to Intelligent Transportation System(ITS) through its ability to provide flexibility and programmability through a logically centralized controlled cluster that has a full comprehension of view of the network. However, as the SDN paradigm is currently studied in vehicular ad hoc networks(VANETs), adapting it to work on cloud-based vehicular network requires some changes to address particular computation features such as task computation of applications of cloud-based vehicular networks. There has been initial work on briging SDN concepts to vehicular networks to reduce the latency by using the fog computing technology, but most of these studies do not directly tackle the issue of task computation. This paper proposes a Software-Defined Cloud-based vehicular Network called SDCVN framework. In this framework, we study the effectiveness of task computation of applications of cloud-based vehicular networks with vehicular cloud and roadside edge cloud. Considering the edge cloud service migration due to the vehicle mobility, we present an efficient roadside cloud based controller entity scheme where the tasks are adaptively computed through vehicular cloud mode or roadside computing predictive trajectory decision mode. Simulation results show that our proposal demonstrates a stable and low route setup time in case of installing the forwarding rules of the routing applications because the source node needs to contact the controller once to setup the route.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.05a
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• pp.238-240
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• 2018

Cloud vehicular networks are a promising paradigm to improve vehicular through distributing computation tasks between remote clouds and local vehicular terminals. Software-Defined Network(SDN) can bring advantages to Intelligent Transportation System(ITS) through its ability to provide flexibility and programmability through a logically centralized controlled cluster that has a full comprehension of view of the network. However, as the SDN paradigm is currently studied in vehicular ad hoc networks(VANETs), adapting it to work on cloud-based vehicular network requires some changes to address particular computation features such as task computation of applications of cloud-based vehicular networks. There has been initial work on briging SDN concepts to vehicular networks to reduce the latency by using the fog computing technology, but most of these studies do not directly tackle the issue of task computation. This paper proposes a Software-Defined Cloud-based vehicular Network called SDCVN framework. In this framework, we study the effectiveness of task computation of applications of cloud-based vehicular networks with vehicular cloud and roadside edge cloud. Considering the edge cloud service migration due to the vehicle mobility, we present an efficient roadside cloud based controller entity scheme where the tasks are adaptively computed through vehicular cloud mode or roadside computing predictive trajectory decision mode. Simulation results show that our proposal demonstrates a stable and low route setup time in case of installing the forwarding rules of the routing applications because the source node needs to contact the controller once to setup the route.

• Journal of the Korean Society for Precision Engineering
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• v.17 no.9
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• pp.181-188
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• 2000

This paper deals with an analysis of the compliance characteristic for effective peg-in-hole task using robot hand without inter-finger coupling. We first observe the fact that some of coupling stiffness elements cannot be planned arbitrary. next we classify the task of inserting a peg-in-a-hole into two contact styles between the peg and the hole. Then we analyze the conditions of the specified stiffness matrix in the operational space to successfully and more effectively achieve the give peg-in-hole task for each case. It is concluded that the location of compliance center on the peg and the coupling stiffness element existing between the translational and the rotational direction play important roles for successful peg-in-hole task. Simulation results are included to verify the feasibility of the analytic results.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.8
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• pp.656-664
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• 2016

While anthropomorphic robots are gaining interest, dual-arm robots are widely used in the industrial environment. Many methods exist in order to implement bimanual tasks by dual-arm robot. However, kinesthetic teaching is used in this paper. This paper suggests three different kinesthetic teaching methods that can implement most of the human task by the robot. The three kinesthetic teaching methods are joint level, task level, and contact level teaching. The task introduced in this paper is box packing, which is a popular and complex task in industrial environment. The task is programmed into the dual-arm robot by utilizing the suggested kinesthetic teaching method, and this paper claims that most tasks can be implemented by using the suggesting kinesthetic teaching methods.