• KIPS Transactions on Software and Data Engineering
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• v.6 no.12
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• pp.549-564
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• 2017

Not only services that are provided by a single system have been various with the development of the Internet of Things and autonomous software but also new services that are not possible before are provided through collaboration between systems. The collaboration between autonomous systems is similar to the ecosystem configuration in terms of biological viewpoints. Thus, it is called the IT Ecosystem, and this concept has arisen newly in recent years. The IT Ecosystem refers to a concept that achieves a mission of each of a number of heterogeneous systems rather than a single system utilizing their own autonomy as well as achieving the objectives of the overall system simultaneously in order to meet a single common goal. In our previous study, we proposed architecture of elementary level and as well as basic several meta-models to implement the IT Ecosystem. This paper proposes comprehensive reference architecture framework to implement the IT Ecosystem by cleansing the previous study. Among them, a utility function based on cost-benefit model is proposed to solve the dynamic re-configuration problem of system components. Furthermore, a measure of using genetic algorithm is proposed as a solution to reduce the dynamic re-configuration overhead that is increased exponentially according to the expansion of the number of entities of components in the IT Ecosystem. Finally, the utilization of the proposed orchestration framework is verified quantitatively through probable case studies on IT Ecosystem for unmanned forestry management.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.6
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• pp.639-645
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• 2018

This paper is intended to develop a decision model that can be applied to autonomous vehicles and autonomous mobile vehicles. The developed module has an independent configuration for application in various driving environments and is based on a platform for organically operating them. Each module is studied for decision making on lane changes and for securing safety through reinforcement learning using a deep learning technique. The autonomous mobile moving body operating to change the driving state has a characteristic where the next operation of the mobile body can be determined only if the definition of the speed determination model (according to its functions) and the lane change decision are correctly preceded. Also, if all the moving bodies traveling on a general road are equipped with an autonomous driving function, it is difficult to consider the factors that may occur between each mobile unit from unexpected environmental changes. Considering these factors, we applied the decision model to the platform and studied the lane change decision system for implementation of the platform. We studied the decision model using a modular learning method to reduce system complexity, to reduce the learning time, and to consider model replacement.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.1541-1544
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• 1997

The rehailitation robot, one of the service robot, is the important area in the service automation. In the paper, we describe the overall configuration of KARES(KAIST Rehabilitation Engineering System), which is an intellingent rehabilitaion robotic system designed to assist the independent livelihood of the handicapped and the eldrly. KARES consists of the 6 degree of freedom robot arm mounted on a wheelchair, the controller ofr the arm, sensors to perceive environment, and user interface. Basic desired hobs in KARES are gripping the target object and moving it to the user's face for eating, drinking, or cooperation work wiht the mouth. Currently, the manual operation of the arm is available for gripping to target objects. The autonomous functionality will be ginven for the facilities of the human operator.

• International journal of advanced smart convergence
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• v.6 no.4
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• pp.73-79
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• 2017

The Convolutional Neural Network (CNN) has shown an excellent performance in computer vision task. Applications of CNN include image classification, object detection in images, autonomous driving, etc. This paper will evaluate the performance of CNN model with ReLU and SELU as activation function. The evaluation will be performed on four different choices of hyperparameter which are initialization method, network configuration, optimization technique, and regularization. We did experiment on each choice of hyperparameter and show how it influences the network convergence and test accuracy. In this experiment, we also discover performance improvement when using SELU as activation function over ReLU.

• Proceedings of the KIEE Conference
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• 2006.04a
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• pp.93-95
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• 2006

In many control system applications, the system designed must not only satisfy the damping and accuracy specifications, but the control must also yield performance that is robust to external disturbance and parameter variations. We have shown that feedback in conventional control systems has the inherent ability of reducing the effects of external disturbance and parameter variations. Unfortunately, robustness with the conventional feedback configuration is achieved only with a high loop gain, which is normally detrimental to stability. The design of intelligent, autonomous machines to perform tasks that are dull, repetitive, hazardous, or that require skill, strength, or dexterity beyond the capability of humans is the ultimate goal of robotics research. This paper prove the robust control using Analog Adaptive Resonance Theorv(ART2) Algorithm about case study.

• Journal of Korea Society of Digital Industry and Information Management
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• v.9 no.1
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• pp.73-78
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• 2013

In this paper, configuration control for the Horizontal Maintenance of the 2 wheel robot has been studied using ARS(Attitude Refrence System). The 2 wheel robot technique is getting attention and there have been many researches on the seg-way since the US. Using its 2 freedom, a 2 wheel robot can move in various modes and Our robot performs goal reaching ARS.2 wheel robot fall down to the forward or reverse direction to converge to the stable point. Kalman Filter is normally used for the algorithm and numerous research is progressing at the moment. To calculate the attitude in ARS using 2 axis gyro(roll, pitch) and 3 axis accelerometers (x, y, z). In this paper we present a two wheel robot system for an autonomous mobile robot. This paper realized the robot control method which is much simpler but able to get desired performance by using the ARS control.

• Architectural research
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• v.26 no.1
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• pp.1-12
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• 2024

This study introduces a deep reinforcement learning (DRL)-based methodology for optimizing apartment space arrangements, addressing the limitations of human capability in evaluating all potential spatial configurations. Leveraging computational power, the methodology facilitates the autonomous exploration and evaluation of innovative layout options, considering architectural principles, legal standards, and client re-quirements. Through comprehensive simulation tests across various apartment types, the research demonstrates the DRL approach's effec-tiveness in generating efficient spatial arrangements that align with current design trends and meet predefined performance objectives. The comparative analysis of AI-generated layouts with those designed by professionals validates the methodology's applicability and potential in enhancing architectural design practices by offering novel, optimized spatial configuration solutions.

• Journal of Digital Convergence
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• v.13 no.1
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• pp.297-304
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• 2015

Recently, the demand for a PRT(Personal Rapid Transit) system based on autonomous navigation is increasing. Accordingly, the applicability investigations of the PRT system on rail tracks or roadways have been widely studied. In the case of unmanned vehicle operations without physical guideways on roadways, to monitor the position of the vehicle in real time is very important for stable, robust and reliable guidance of an autonomous vehicle. The Global Positioning System (GPS) has been commercially used for vehicle positioning. However, it cannot be applied in environments as tunnels or interiors of buildings. The PRT navigation system based on magnetic markers reference sensing that can overcome these environmental restrictions and the vehicle dynamics model for its H/W configuration are presented in this study. In addition, the design of a control S/W dedicated for unmanned operation of a PRT vehicle and its prototype implementation for experimental validation on a pilot network were successfully achieved.

• Journal of the Institute of Electronics and Information Engineers
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• v.54 no.6
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• pp.106-113
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• 2017

In this paper, we propose a suitable network topology for the Ethernet based Train Communication Network (TCN) for control system in a autonomous multi-articulated vehicle. We propose a network topology considering the structural constraints such as the number of cables and ports, and the performance constraints such as network response time and maximum throughput. We compare the network performances of star topology and daisy chain topology as well as hybrid topology, which is proposed in previous studies and a compromise between daisy chain and star topology. Here, the appropriate number of nodes in a group is obtained for the configuration of the hybrid topology. We first derive estimates of the network performance through simulation with different topologies, and then, implement the network by connecting the actual devices with each network topology. The performance of each topology is measured using various network performance measurement programs and the superiority of the proposed topology is described through comparison.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.3
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• pp.427-432
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• 2023

In this study, MEC (: Multi-access Edge Computing) proposes a cloud service network configuration for various tests of autonomous vehicles to which V2X (: Vehicle to Everything) is applied in Wave, LTE, and 5G networks and MEC App (: Application) applied V2X service function test verification of two domains (operator (KT, SKT, LG U+), network type (Wave, LTE (including 3G), 5G)) in a specific region. In 4G networks of domestic operators (SKT, KT, LG U+ and Wave), MEC summarized the improvement effects through V2X function blocks and traffic offloading for the purpose of bringing independent network functions. And with a high level of QoS value in the V2X VNF of the 5G network, the traffic steering function scenario was demonstrated on the destination-specific traffic path.