• Proceedings of the Korean Society of Precision Engineering Conference
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• 2011.06a
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• pp.79-80
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• 2011

• Journal of Navigation and Port Research
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• v.28 no.1
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• pp.9-16
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• 2004

The purpose of this study is to examine the algorithm of ship collision avoidance system and to improve its performance. The study on the algorithm of ship collision avoidance system have been carried out by many researchers. We can divide the study according to the adopted theory into two category such as 'collision risk calculation method' and 'risk area method'. It is not so difficult to find heir merit and demerit in the respective method. This study suggested newly modified model, which can overcome a limit in the two method. The suggested model is based on collision risk calculation method and suggests how to solve the threshold value problem, that is, one of the unsolved issues in collision risk calculation method. To solve that problem this study proposed new system under which the users can select appropriate threshold value according to environments such as traffic situations and weathers conditions. Simulation results of new model is schematized using 'risk area method'to examine the relationships between the two method. In addition, in case of 'collision risk method', when TCPA and DCPA are used to determine collision risk, a problem happens, that is, two ships become too close in their stem area, therefore, partial function of 'risk area method'is adopted to solve the problem in suggested model.

• 한국항공운항학회:학술대회논문집
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• 2016.05a
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• pp.196-196
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• 2016

본 논문에서는 수직 회피에 사용되고 있는 Traffic Alert and Collision Avoidance System(TCAS)와 수평 회피 알고리즘을 객체지향 언어로 구현하였고, 구현된 소프트웨어의 검증을 위해 Intel-core i5-4세대 프로세서와 8GB의 메모리카드 그리고 Window7 OS 환경에서 확인하였다.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.908-911
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• 1996

본 논문은 작업공간을 공유하는 두 대의 스카라 로봇으로 이루어진 Dual-Arm SCARA 로봇 시스템과 여러 대의 로봇을 제어할수 있는 로봇제어기로 동시에 독립적인 작업을 하는 경우 두 로봇의 동작에 따른 로봇 ARM의 모델링을 실시간으로 처리하여 상대 로봇과의 충돌이 예상되는지를 실시간 검색하여 두 로봇간의 충돌이 발생하지 않도록 하는 충돌검출 방법과, 두 대의 로봇이 충돌가능성으로 인하여 원하는 작업을 수행할수 없는 상태가 되는 경우 작업을 원활하게 이루어지도록 하는 충돌회피를 위한 로봇의 궤적을 생성하여 로봇을 이동시키고 다시 원래의 위치로 돌아 올수 있는 방법을 구현하였다.

• 제어로봇시스템학회:학술대회논문집
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• 1990.10a
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• pp.388-393
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• 1990

A robot manipulator and an obstacle are described mathematically in joint space, with the mathematical representation for the collision between the robot manipulator and the obstacle. Using these descriptions, the robot motion planning problem is formulated which can be used to avoide a time varying obstacle. To solve the problem, the constraints on motion planning are discretized in joint space. An analytical method is proposed for planning the motion in joint space from a given starting point to the goal point. It is found that solving the inverse kinematics problem is not necessary to get the control input to the joint motion controller for collision avoidance.

• Journal of Electrical Engineering and Technology
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• v.12 no.2
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• pp.890-903
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• 2017

The problem of determining a smooth and collision-free path with maximum possible speed for a Mobile Robot (MR) which is chasing a moving target in a dynamic environment is addressed in this paper. Genetic Network Programming with Reinforcement Learning (GNP-RL) has several important features over other evolutionary algorithms such as it combines offline and online learning on the one hand, and it combines diversified and intensified search on the other hand, but it was used in solving the problem of MR navigation in static environment only. This paper presents GNP-RL based on predicting collision positions as a first attempt to apply it for MR navigation in dynamic environment. The combination between features of the proposed collision prediction and that of GNP-RL provides safe navigation (effective obstacle avoidance) in dynamic environment, smooth movement, and reducing the obstacle avoidance latency time. Simulation in dynamic environment is used to evaluate the performance of collision prediction based GNP-RL compared with that of two state-of-the art navigation approaches, namely, Q-Learning (QL) and Artificial Potential Field (APF). The simulation results show that the proposed GNP-RL outperforms both QL and APF in terms of smooth movement and safer navigation. In addition, it outperforms APF in terms of preserving maximum possible speed during obstacle avoidance.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2013.10a
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• pp.167-170
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• 2013

The objective of this paper is to describe the result of development of collision avoidance supporting system, based on the electronic chart display and information system(ECDIS). In real ship operations, collision accidents happen frequently due to human errors such as the lax vigilance, misinterpretation of international regulations for preventing collisions at sea (COLREGs). We developed a system which will help to avoid these kind of accidents. This system can automatically recognize the risk of collisions, generate the safe alternative routes that comply with COLREGs, and then deliver the results into auto pilot. A virtual simulation assuming progressive collision situations revealed the usefulness of this system.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1927-1932
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• 2003

In a previous study, the authors have proposed the Cooperative Collision Avoidance (CCA) method which enables mobile robots to cooperatively avoid collisions, by extending the concept of the Velocity Obstacle to multiple robot systems. The method introduced an evaluation function considering an operation objective so that each robot can choose the velocity which optimizes the function. As the evaluation function could be of an arbitrary type, this method is applicable to a wide variety of tasks. However, it complicates the optimization of the function especially in real-time. In addition, construction of the evaluation function requires an operation objective of the other robot which is very hard to obtain without communication. In this paper, the CCA method is improved considering such problems for implementation. To decrease computational costs, the previous method is simplified by introducing two essential assumptions. Then, by treating the desired direction of locomotion for each robot as the operation objective, an operation objective estimator which estimates the desired direction of the other robot is introduced. The only measurement required is the other robot's relative position, since the other information can be obtained through the estimation. Hence, communicational devices that are necessary for most other cooperative methods are not required. Moreover, mobile robots employing the method can avoid collisions with uncooperative robots or moving obstacles as well as with cooperative robots. Consequently, this improved method can be applied to general dynamic environments consisting of various mobile robots.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.1
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• pp.240-257
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• 2022

Autonomous vehicles use various local sensors such as camera, radar, and lidar to perceive the surrounding environment. However, it is difficult to predict the movement of vulnerable road users using only local sensors that are subject to limits in cognitive range. This is true especially when these users are blocked from view by obstacles. Hence, this paper developed an algorithm for collision avoidance with VRU using V2X information. The main purpose of this collision avoidance system is to overcome the limitations of the local sensors. The algorithm first evaluates the risk of collision, based on the current driving condition and the V2X information of the VRU. Subsequently, the algorithm takes one of four evasive actions; steering, braking, steering after braking, and braking after steering. A simulation was performed under various conditions. The results of the simulation confirmed that the algorithm could significantly improve the performance of the collision avoidance system while securing vehicle stability during evasive maneuvers.

• Journal of the Korean Society of Marine Environment & Safety
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• v.25 no.2
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• pp.178-188
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• 2019

When using a distributed system, it is very important to know the intention of a target ship in order to prevent collisions. The action taken by a certain ship for collision avoidance and the action of the target ship it intends to avoid influence each other. However, it is difficult to establish a collision avoidance plan in consideration of multiple-ship situations for this reason. To solve this problem, a Distributed Stochastic Search Algorithm (DSSA) has been proposed. A DSSA searches for a course that can most reduce cost through repeated information exchange with target ships, and then indicates whether the current course should be maintained or a new course should be chosen according to probability and constraints. However, it has not been proven how the parameters used in DSSA affect collision avoidance actions. Therefore, in this paper, I have investigated the effect of the parameters and weight factors of DSSA. Experiments were conducted by combining parameters (time window, safe domain, detection range) and weight factors for encounters of two ships in head-on, crossing, and overtaking situations. A total of 24,000 experiments were conducted: 8,000 iterations for each situation. As a result, no collision occurred in any experiment conducted using DSSA. Costs have been shown to increase if a ship gives a large weight to its destination, i.e., takes selfish behavior. The more lasting the expected position of the target ship, the smaller the sailing distance and the number of message exchanges. The larger the detection range, the safer the interaction.