• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.104.3-104
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• 2002

A quadruped stair robot introduced here plays a role in monitoring and moving some place where an operator can not reach or when he may not keep watching. It has several features that travels and poses variable position by four caterpillars and quadruped typed arms, transmits an image and command data via RF wireless and network communication. The robot can balance itself when it moves up and down on a slope by using the quadruped mechanism. The robot vision scans ahead before it moves, and the captured image is transferred to a main computer via a RF image module. The main computer analyzes the obstacle, and when it is found the obstacle, the robot avoids from the obstacle and keep moving f...

• Electronics and Telecommunications Trends
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• v.35 no.4
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• pp.81-90
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• 2020

The use of machine learning technologies such as deep and reinforcement learning has proliferated in various domains with the advancement of deep neural network studies. To make the learning successful, both big data acquisition and fast processing are required. However, for some physical world applications such as autonomous drone flight, it is difficult to achieve efficient learning because learning with a premature A.I. is dangerous, cost-ineffective, and time-consuming. To solve these problems, simulation-based approaches can be considered. In this study, we analyze recent trends in drone simulation technologies and compare their features. Subsequently, we introduce Octopus, which is a highly precise and scalable drone simulator being developed by ETRI.

• Asia pacific journal of information systems
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• v.13 no.2
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• pp.145-170
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• 2003

Open Decision Support System(DSS) is an automated and transparent system that is built to be shared both within and across organizations. The open DSS has been thought to be a set of decision components that are communicating through Web protocols. These characteristics intuitively invite the Web services concepts, which are currently one of the new trends in network-based business services. However, web services still are not active enough to be autonomous, and to provide for composing functionalities. These lead to the motivation on building a sophisticated web service to contain these features and to utilize web services on behalf of the user. This paper aims to propose a new concept of Meta Web Service, a web service-based open DSS. Decision modules in a dynamic and open DSS can be viewed as a web service. The Meta Web Service understands the users problem statement with ontology, performs web service discovery, web service composition, and automatically generates codes for composite web service execution. A prototype of example web service has been developed to show the feasibility of the proposed idea.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2006.05a
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• pp.1235-1239
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• 2006

Fractal manufacturing system (FrMS) distinguishes itself from other manufacturing systems by the fact that there is a fractal repeated at every scale. A fractal is a volatile organization which consists of goal-oriented agents referred to as AIR-units (autonomous and intelligent resource units). AIR-units unrestrictedly reconfigure fractals in accordance with their own goals. Their goals can be dynamically changed along with the environmental status. Since goals of AIR-units are represented as fuzzy models, an AIR-unit itself is a fuzzy logic controller. This paper presents a goal regulation mechanism in the FrMS. In particular, a reinforcement learning method is adopted as a regulating mechanism of the fuzzy goal model, which uses only weak reinforcement signal. Goal regulation is achieved by building a feedforward neural network to estimate compatibility level of current goals, which can then adaptively improve compatibility by using the gradient descent method. Goal-oriented features of AIR-units are also presented.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.7 no.1
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• pp.41-48
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• 2007

Latest advances in network sensor technology and state of the art of mobile robot, and artificial intelligence research can be employed to develop autonomous and distributed monitoring systems. In this study, as the preliminary step for developing a multi-purpose "Intelligent Space" platform to implement advanced technologies easily to realize smart services to human. We will give an explanation for the ISpace system architecture designed and implemented in this study and a short review of existing techniques, since there exist several recent thorough books and review paper on this paper. Instead we will focus on the main results with relevance to the DIND data fusion with CI of Intelligent Space. We will conclude by discussing some possible future extensions of ISpace. It is first dealt with the general principle of the navigation and guidance architecture, then the detailed functions tracking multiple objects, human detection and motion assessment, with the results from the simulations run.

• Asian Journal of Innovation and Policy
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• v.9 no.2
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• pp.145-163
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• 2020

The COVID-19 is a pandemic that affects all facets of our life and will change many patterns in science technology and innovation. A qualitative study was conducted using Focus Group Interview involving ten industry-academia-research experts with the objective of identifying changes in Korea's national innovation system and science & technology policy after the COVID-19. Eight questions were designed, based on the major components of the national innovation system, such as companies, universities, and research institutes, to discuss the changes in the national innovation system and science & technology policy. Also, keyword analysis and cluster analysis were performed using the network analysis program VOSviewer. It is predicted that, in the wake of the COVID-19, Korea's national innovation system will shift to a new paradigm that is more decentralized, responsive, and autonomous. Furthermore, several policy agendas that can turn these changes into positive momentum of change in science & technology policy are presented.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.12
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• pp.4489-4501
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• 2014

We propose a novel lane detection method based on classification in image sequences. Both structural and statistical features of the extracted bright shape are applied to the neural network for finding correct lane marks. The features used in this paper are shown to have strong discriminating power to locate correct traffic lanes. The traffic lanes detected in the current frame is also used to estimate the traffic lane if the lane detection fails in the next frame. The proposed method is fast enough to apply for real-time systems; the average processing time is less than 2msec. Also the scheme of the local illumination compensation allows robust lane detection at nighttime. Therefore, this method can be widely used in intelligence transportation systems such as driver assistance, lane change assistance, lane departure warning and autonomous vehicles.

• Journal of the Korean Society of Industry Convergence
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• v.18 no.1
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• pp.10-17
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• 2015

We describe a research about remote control of mobile robot based on voice command in this paper. Through real-time remote control and wireless network capabilities of an unmanned remote-control experiments and Home Security / exercise with an unmanned robot, remote control and voice recognition and voice transmission are possible to transmit on a PC using a microphone to control a robot to pinpoint of the source. Speech recognition can be controlled robot by using a remote control. In this research, speech recognition speed and direction of self-driving robot were controlled by a wireless remote control in order to verify the performance of mobile robot with two drives.

• Journal of the Semiconductor & Display Technology
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• v.19 no.3
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• pp.124-129
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• 2020

Autonomous underwater vehicle makes attracts to many researchers. This paper proposes a convolutional neural network (CNN) based fish detection method. Since there are not enough data sets in the process of training, overfitting problem can be occurred in deep learning. To solve the problem, we apply the dropout algorithm to simplify the model. Experimental result showed that the implemented method is promising, and the effectiveness of identification by dropout approach is highly enhanced.

• Electronics and Telecommunications Trends
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• v.32 no.6
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• pp.57-65
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• 2017

Neural network based AI computing is a promising technology that reflects the recognition and decision operation of human beings. Early AI computing processors were composed of GPUs and CPUs; however, the dramatic increment of a floating point operation requires an energy efficient AI processor with a highly parallelized architecture. In this paper, we analyze the trends in processor architectures for AI computing. Some architectures are still composed using GPUs. However, they reduce the size of each processing unit by allowing a half precision operation, and raise the processing unit density. Other architectures concentrate on matrix multiplication, and require the construction of dedicated hardware for a fast vector operation. Finally, we propose our own inAB processor architecture and introduce domestic cutting-edge processor design capabilities.