• International Journal of Fuzzy Logic and Intelligent Systems
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• v.14 no.4
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• pp.288-294
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• 2014

Understanding a ship's present position has been one of the most important tasks during a ship's voyage, in both ancient and modern times. Particularly, a ship's dead reckoning (DR) has been used for predicting traffic situations and collision avoidance actions. However, the current system that uses the traditional method of calculating DR employs the received position and speed data only. Therefore, it is not applicable for predicting navigation within the harbor limits, owing to the frequent changes in the ship's course and speed in this region. In this study, planned routes were applied for improving the reliability of the proposed system and predicting the traffic patterns in advance. The proposed method of determining the dead reckoning position (DRP) uses not only the ships' received data but also the navigational patterns and tracking data in harbor limits. The Mercator sailing formulas were used for calculating the ships' DRPs and planned routes. The data on the traffic patterns were collected from the automatic identification system and analyzed using MATLAB. Two randomly chosen ships were analyzed for simulating their tracks and comparing the DR method during the timeframes of the ships' movement. The proposed method of calculating DR, combined with the information on planned routes and DRPs, is expected to contribute towards improving the decision-making abilities of operators.

• ETRI Journal
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• v.37 no.6
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• pp.1108-1119
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• 2015

Multicast communication of mobile ad hoc networks is vulnerable to internal attacks due to its routing structure and high scalability of its participants. Though existing intrusion detection systems (IDSs) act smartly to defend against attack strategies, adversaries also accordingly update their attacking plans intelligently so as to intervene in successful defending schemes. In our work, we present a novel indirect internal stealthy attack on a tree-based multicast routing protocol. Such an indirect stealthy attack intelligently makes neighbor nodes drop their routing-layer unicast control packets instead of processing or forwarding them. The adversary targets the collision avoidance mechanism of the Medium Access Control (MAC) protocol to indirectly affect the routing layer process. Simulation results show the success of this attacking strategy over the existing "stealthy attack in wireless ad hoc networks: detection and countermeasure (SADEC)" detection system. We design a cross-layer automata-based stealthy attack on multicast routing protocols (SAMRP) attacker detection system to identify and isolate the proposed attacker. NS-2 simulation and analytical results show the efficient performance, against an indirect internal stealthy attack, of SAMRP over the existing SADEC and BLM attacker detection systems.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.11
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• pp.904-911
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• 2016

This paper presents a novel driving system by the humanoid robot to drive a vehicle in disaster response situations. To enhance robot's capability for substituting human activities in responding to natural and man-made disaster, the one of prerequisite skills for the rescue robot is the mounted mobility to maneuver a vehicle safely in disaster site. Therefore, our driving system for the humanoid is developed in order to steer a vehicle through unknown obstacles even under poor communication conditions such as time-delay and black-out. Especially, the proposed system includes a tele-manipulation interface and stable navigation strategies. First, we propose a new type of path estimation method to overcome limited communication. Second, we establish navigation strategies when the operator cannot recognize obstacles based on Dynamic Window Approach. The effectiveness of the proposed developments is verified through simulation and experiments, which demonstrate suitable system for driving a vehicle in disaster response.

• Journal of the Korean Institute of Intelligent Systems
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• v.23 no.2
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• pp.100-106
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• 2013

This paper presents design and control of an 'Omni-directional Cleaning Robot (OdCR)' which employs omni-wheels at three edges of its triangular configuration. Those omni-wheels enable the OdCR to move in any directions so that lateral movement is possible. For OdCR to be localized, a StarGazer sensor is used to provide accurate position and heading angle based on landmarks on the ceiling. In addition to that, ultrasonic sensors are installed to detect obstacles around OdCR's way. Experimental studies are conducted to test the functionality of the system.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.10a
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• pp.873-874
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• 2015

본 논문에서는 24~77GHz 대역의 충돌 방지 레이더 센서를 이용한 차량 충돌 방지 알고리즘을 제안한다. 제안한 알고리즘은 센서로 부터 측정한 전압을 이용하여 전/후/좌/우의 차량의 접근 정보를 획득하고 이를 효율적으로 이용하여 다양한 상황에 따른 차량충돌방지를 할 수 있도록 구현되어 있다. 제안한 차량 충돌방지 알고리즘은 운행 중인 속도를 기반으로 속도구간별 운행정보를 계산하여 충돌방지를 실행한다. 본 연구에서 구현한 차량 충돌 방지 알고리즘은 차량 주행에서 좌우 차량충돌 없이 효율적으로 운행하는 특성을 보였다.

• Journal of Korea Game Society
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• v.20 no.3
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• pp.85-94
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• 2020

AI-based smart factory technologies are only increase short-term productivity. To solve this problem, collaborative intelligence combines human teamwork, creativity, AI speed, and accuracy to actively compensate for each other's shortcomings. However, current automation equipmens require high safety measures due to the high disaster intensity in the event of an accident. In this paper, we design and implement a factory safety control system that uses a depth camera to implement workers and facilities in the virtual world and to determine the safety of workers through simulation.

• Proceedings of the Korea Information Processing Society Conference
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• 2015.10a
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• pp.387-389
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• 2015

IEEE 802.11e EDCA(Enhanced Distributed Channel Access)는 4개의 AC(Access Category)를 이용하여 트래픽에 따른 우선순위를 부여하고 QoS(Quality of Service)를 제공하기 위해 표준화되었다. EDCA는 이진 백오프 알고리즘을 갖는 CSMA/CA(Carrier Sense Multiple Access with Collision Avoidance) 방법을 이용한다. EDCA에서 패킷 전송에 실패할 경우 경쟁 윈도우 값은 두 배씩 증가 되고, 성공할 경우에는 최소 경쟁 윈도우 값으로 초기화된다. 따라서 경쟁 윈도우 값이 최적의 값을 유지하지 못해 많은 패킷 충돌을 야기하여 네트워크 성능을 감소시킨다. 이 문제를 해결하기 위해 기존에 제안된 논문에서는 패킷 전송 성공 후 경쟁 윈도우 값을 최소 경쟁 윈도우 값이 아닌 채널 혼잡 정도에 따라 계산된 값으로 설정한다. 그러나 이 방법은 트래픽 종류와 상관없이 같은 방법으로 동작하기 때문에 트래픽 종류에 따른 차별적 QoS를 보장하지 않는다. 또한 계산된 경쟁 윈도우 값은 현재 값에 비해 상대적으로 낮은 값을 갖기 때문에 여전히 높은 충돌율을 갖는다. 본 논문에서는 이 문제를 해결하기 위해 새로운 프로토콜을 제안한다. 제안된 방법에서는 네트워크의 혼잡 정도를 잘 반영하기 위한 새로운 경쟁 윈도우 계산 알고리즘을 제시한다. 또한 제안된 알고리즘은 트래픽 종류에 따른 QoS 보장을 위해 트래픽 종류에 따른 차별화 파라미터를 이용한다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.05a
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• pp.765-767
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• 2014

본 논문에서는 단거리 레이더용 차량 추돌 방지 24-GHz CMOS 고주파 전력 증폭기 (RF Power Amplifier)를 제안한다. 이러한 회로는 class-A 모드 증폭기로서 단간 (inter-stages) 공액 정합 (conjugate matching) 회로를 가진 공통-소스 단으로 구성되어 있다. 칩 면적을 줄이기 위해 실제 인덕터 대신 전송선(Transmission Line)을 이용하였다. 제안한 회로는 TSMC $0.13{\mu}m$ 혼성 신호/고주파 CMOS 공정 ($f_T/f_{MAX}=120/140GHz$)으로 설계하였다. 설계한 CMOS 고주파 전력 증폭기는 최근 발표된 연구결과에 비해 약 22dB의 높은 전력이득 및 7.1%의 높은 PAE 특성을 보였다.

• Ocean Systems Engineering
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• v.10 no.4
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• pp.415-434
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• 2020

Detecting objects is important for the safe operation of ships, and enables collision avoidance, risk detection, and autonomous sailing. This study proposes a ship detection method from images and videos taken at sea using one of the state-of-the-art deep neural network-based object detection algorithms. A deep learning model is trained using a public maritime dataset, and results show it can detect all types of floating objects and classify them into ten specific classes that include a ship, speedboat, and buoy. The proposed deep learning model is compared to a universal trained model that detects and classifies objects into general classes, such as a person, dog, car, and boat, and results show that the proposed model outperforms the other in the detection of maritime objects. Different deep neural network structures are then compared to obtain the best detection performance. The proposed model also shows a real-time detection speed of approximately 30 frames per second. Hence, it is expected that the proposed model can be used to detect maritime objects and reduce risks while at sea.

• Journal of the Korean Society of Industry Convergence
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• v.25 no.5
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• pp.853-859
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• 2022

In this study, we analyzed the instantaneous trajectory generation capability and target arrival rate of a mobile robot by changing the parameter of the TEB (Timed Elastic Band) Local Planner among local planners that affect the instantaneous obstacle avoidance ability of the mobile robot using ROS (Robot Operating System) simulation and real experience. As a result, we can expect a decrease in the target arrival time of the mobile robot through a decrease in the parameter values of the TEB Local Planner's min_obstacle_dist, inflation_dist, and penalty_epsilon. However, if this parameter is reduced too much, the risk of obstacle collision of the moving robot is increases, so it is important to combine the appropriate values to construct the parameter.