• The Journal of Korea Robotics Society
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• v.11 no.3
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• pp.172-182
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• 2016

Lane-level vehicle positioning is an important task for enhancing the accuracy of in-vehicle navigation systems and the safety of autonomous vehicles. GPS (Global Positioning System) and DGPS (Differential GPS) are generally used in navigation service systems, which however only provide an accuracy level up to 2~3 m. In this paper, we propose a 3D vision based lane-level positioning technique which can provides accurate vehicle position. The proposed method determines the current driving lane of a vehicle by tracking the 3D position of traffic signs which stand at the side of the road. Using a stereo camera, the 3D tracking paths of traffic signs are computed and their projections to the 2D road plane are used to determine the distance from the vehicle to the signs. Several experiments are performed to analyze the feasibility of the proposed method in many real roads. According to the experimental results, the proposed method can achieve 90.9% accuracy in lane-level positioning.

• The Journal of Korea Robotics Society
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• v.12 no.4
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• pp.402-410
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• 2017

Acoustic based localization is essential to operate autonomous robotic systems in underwater environment where the use of sensorial data is limited. This paper proposes a localization method using artificial underwater acoustic sources. The proposed method acquires directional angles of acoustic sources using time difference of arrivals of two hydrophones. For this purpose, a probabilistic approach is used for accurate estimation of the time delay. Then, Gaussian sum filter based SLAM technique is used to localize both acoustic sources and underwater vehicle. It is performed by using bearing of acoustic sources as measurement and inertial sensors as prediction model. The proposed method can handle directional ambiguity of time difference based source localization by generating Gaussian models corresponding to possible locations of both front and back sides. Through these processes, the proposed method can provide reliable localization method for underwater vehicles without any prior information of source locations. The performance of the proposed method is verified by experimental results conducted in a real sea environment.

• Proceedings of the IEEK Conference
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• summer
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• pp.421-426
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• 2004

Analyzing adaptive possibilities of agents in multi-agents system, we have discovered new aspects of ambient intelligence in distributed modular systems using intelligent building blocks (I-BLOCKS) [1]. This paper describes early scientific researches related to technical design, applicable experiments and evaluation of adaptive processing and information interaction among I-BLOCKS allowing users to easily develop ambient intelligence applications. The processing technology presented in this paper is embedded inside each DUPLO1 brick by microprocessor as well as selected sensors and actuators in addition. Behaviors of an I-BLOCKS modular structure are defined by the internal processing functionality of each I-Blocks in such structure and communication capacities between I-BLOCKS. Users of the I-BLOCKS system can do 'programming by building' and thereby create specific functionalities of a modular structure of intelligent artefacts without the need to learn and use traditional programming language. From investigating different effects of modem artificial intelligence, I-BLOCKS we have developed might possibly contain potential possibilities for developing applications in ambient intelligence (AmI) environments. To illustrate these possibilities, the paper presents a range of different experimental scenarios in which I-BLOCKS have been used to set-up reconfigurable modular systems. The paper also reports briefly about earlier experiments of I-BLOCKS in different research fields, allowing users to construct AmI applications by a just defined concept of modular artefacts [3].

• Journal of the Economic Geographical Society of Korea
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• v.18 no.2
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• pp.152-167
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• 2015

This paper analyzes the effects of globalization on growth gaps between regions. Using openness and FDI as measures of globalzation in Korean 16 broad autonomous territories the study estimates the effects of the variables on growth gaps between regions. Estimation results show that FDI is significant in explaining the regional gaps while openness is not. The results of the study reveal that attracting FDI to weaker regions, especially the investment in New Industries, is inevitable to resolve growth gaps and for balanced growth among regions. Also, policy makers should use FDI as an important tool for correcting regional gaps as well as the vehicles for regional development.

• Journal of Digital Contents Society
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• v.18 no.5
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• pp.943-948
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• 2017

Currently, embedded systems designed for specific applications are used extensively in consumer electronics, smart phones, autonomous vehicles, robots, and plant control, etc. In addition, the importance of DRAM, which has a great influence on the performance of an embedded processor constituting an embedded system, has been increasing day by day, and research on DRAM has been actively conducted in industry and academia. Therefore, it is important to have a more accurate DRAM model in order to obtain reliable results when evaluating the performance of an embedded processor through simulation. In this paper, we developed an embedded processor simulator capable of interworking with a DRAM simulator. We also analyzed the influence of the DRAM model, which operates correctly on a cycle-by-cycle basis, on the performance of the embedded processor by using the MiBench embedded benchmark.

• Journal of Ocean Engineering and Technology
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• v.20 no.3 s.70
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• pp.7-14
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• 2006

This paper discusses the structural design and analysis of a 6,000 meters depth-rated capable deep-sea unmanned underwater vehicle (UUV) system. The UUV system is currently under development by Maritime and Ocean Engineering Research Institute(MOERI), Korea Ocean Research and Development Institute (KORDI). The UUV system is composed of three vehicles - a Remotely Operated Vehicle (ROV), an Autonomous Underwater Vehicle (AUV) and a Launcher - which include underwater equipment. The dry weight of the system exceeds 3 tons hence it is necessary to carry out the optimal design of structural system to ensure the minimum weight and sufficient space within the frame for the convenient use of the embedded equipments. In this paper, therefore, the structural design and analysis of the ROV and launcher frame system were carried out, using the optimizing process. The cylindrical pressure vessels for the ROV were designed to resist the extreme pressure of 600 bars, based on the finite element analysis. The collapse pressure for the cylindrical pressure vessels was also checked through a theoretical analysis.

• The Journal of Korea Robotics Society
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• v.11 no.2
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• pp.51-59
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• 2016

In this paper we present (1) analysis of imaging sonar measurement for two-view relative pose estimation of an autonomous vehicle and (2) bundle adjustment and 3D reconstruction method using imaging sonar. Sonar has been a popular sensor for underwater application due to its robustness to water turbidity and visibility in water medium. While vision based motion estimation has been applied to many ground vehicles for motion estimation and 3D reconstruction, imaging sonar addresses challenges in relative sensor frame motion. We focus on the fact that the sonar measurement inherently poses ambiguity in its measurement. This paper illustrates the source of the ambiguity in sonar measurements and summarizes assumptions for sonar based robot navigation. For validation, we synthetically generated underwater seafloor with varying complexity to analyze the error in the motion estimation.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.22 no.4
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• pp.65-74
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• 2014

Unmanned aerial vehicles(UAVs) refer to the aircraft which carries no human pilot and is operated under remote control or in autonomous operational mode. As the UAVs can perform the dull, dangerous and difficult missions, various kinds of UAVs with different sizes and weights have been developed and operated for both civil and military application. As the avionics and communication technology related to the UAVs are matured, the demand for the UAVs is dramatically increased. Therefore, It is important to develope airworthiness process and regulations of the UAVs to minimize related risk to the man and environment. This paper describes related regulations and classification of the small UAVs for different international airworthiness authorities. The analysis of the CS-LURS verses Stanag 4702 and Stanag 4703 can provide guidelines for the generation of the airworthiness certification criteria for the small UAVs in civil sector. This paper conducted kinetic impact energy analysis of the loss of the small UAVs control scenarios and of the very small UAVs under 66 joules. Based on the analysis, the energy impact analysis can be considered before the design certification approval for the small UAVs.

• Journal of the Korea Institute of Military Science and Technology
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• v.13 no.5
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• pp.894-902
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• 2010

This paper presents a vision-based robust off-road terrain classification method against environmental variation. As a supervised classification algorithm, we applied a neural network classifier using wavelet features extracted from wavelet transform of an image. In order to get over an effect of overall image feature variation, we adopted environment sensors and gathered the training parameters database according to environmental conditions. The robust terrain classification algorithm against environmental variation was implemented by choosing an optimal parameter using environmental information. The proposed algorithm was embedded on a processor board under the VxWorks real-time operating system. The processor board is containing four 1GHz 7448 PowerPC CPUs. In order to implement an optimal software architecture on which a distributed parallel processing is possible, we measured and analyzed the data delivery time between the CPUs. And the performance of the present algorithm was verified, comparing classification results using the real off-road images acquired under various environmental conditions in conformity with applied classifiers and features. Experiments show the robustness of the classification results on any environmental condition.

• Journal of information and communication convergence engineering
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• v.11 no.1
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• pp.30-44
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• 2013

Traffic congestion has become a serious problem with the recent exponential increase in the number of vehicles. In urban areas, almost all traffic congestion occurs at intersections. One of the ways to solve this problem is road expansion, but it is difficult to realize in urban areas because of the high cost and long construction period. In such cases, traffic signal control is a reasonable method for reducing traffic jams. In an actual situation, the traffic flow changes randomly and its randomness makes the control of traffic signals difficult. A prediction of traffic jams is, therefore, necessary and effective for reducing traffic jams. In addition, an autonomous distributed (stand-alone) point control of each traffic light individually is better than the wide and/or line control of traffic lights from the perspective of real-time control. This paper describes a stochastic optimum control of crossroads and multi-way traffic signals. First, a stochastic model of traffic flows and traffic jams is constructed by using a Bayesian network. Secondly, the probabilistic distributions of the traffic flows are estimated by using a cellular automaton, and then the probabilistic distributions of traffic jams are predicted. Thirdly, optimum traffic signals of crossroads and multi-way intersection are searched by using a modified particle swarm optimization algorithm to realize real-time traffic control. Finally, simulations are carried out to confirm the effectiveness of the real-time stochastic optimum control of traffic signals.