• 로봇학회논문지
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• 제14권4호
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• pp.285-292
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• 2019

Path planning is an important problem to solve in robotics and there has been many related studies so far. In the previous research, we proposed the Heterogeneous-Ants-Based Path Planner (HAB-PP) for the global path planning of mobile robots. The conventional path planners using grid map had discrete state transitions that constrain the only movement of an agent to multiples of 45 degrees. The HAB-PP provided the smoother path using the heterogeneous ants unlike the conventional path planners based on Ant Colony Optimization (ACO) algorithm. The planner, however, has the problem that the optimization of the path once found is fast but it takes a lot of time to find the first path to the goal point. Also, the HAB-PP often falls into a local optimum solution. To solve these problems, this paper proposes an improved ant-inspired path planner using the Rapidly-exploring Random Tree-star ($RRT^*$). The key ideas are to use $RRT^*$ as the characteristic of another heterogeneous ant and to share the information for the found path through the pheromone field. The comparative simulations with several scenarios verify the performance of the improved HAB-PP.

• 제어로봇시스템학회논문지
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• 제18권3호
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• pp.267-274
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• 2012

We proposed the KPP (Korea university Path Planner) in our previous works. The KPP is the path planning scheme of a car-like mobile robot in parking environment. The objective of this paper is to investigate the advantage of the KPP through the quantitative and qualitative analysis compared with conventional RRT. For comparison, we proposed travel time for performance index. This paper shows that the KPP shows outstanding performances from the viewpoint of travel time and computational efficiency compared with RRT.

• International Journal of Control, Automation, and Systems
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• 제5권6호
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• pp.674-680
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• 2007

The probabilistic roadmap (PRM) method, which is a popular path planning scheme, for a manipulator, can find a collision-free path by connecting the start and goal poses through a roadmap constructed by drawing random nodes in the free configuration space. PRM exhibits robust performance for static environments, but its performance is poor for dynamic environments. On the other hand, reinforcement learning, a behavior-based control technique, can deal with uncertainties in the environment. The reinforcement learning agent can establish a policy that maximizes the sum of rewards by selecting the optimal actions in any state through iterative interactions with the environment. In this paper, we propose efficient real-time path planning by combining PRM and reinforcement learning to deal with uncertain dynamic environments and similar environments. A series of experiments demonstrate that the proposed hybrid path planner can generate a collision-free path even for dynamic environments in which objects block the pre-planned global path. It is also shown that the hybrid path planner can adapt to the similar, previously learned environments without significant additional learning.

• 한국해양공학회:학술대회논문집
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• 한국해양공학회 2006년 창립20주년기념 정기학술대회 및 국제워크샵
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• pp.323-326
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• 2006

The operation planning of multi-AUV is considered as a very difficult task. This paper proposes the qualitative method about the operation plan of multi-agents. In order to achieve this goal, it applies an extension collision map method as a tool to avoide collision between multi AUVs. This tool has been developed for the purpose of collision forecasting and collision avoidance for the multi - agents system in a land where a control is much easier. This paper analyzes the avoidance value of maximum path of AUV in order to apply this to a water environment where a tidal, a wave and disturbances are common. And it suggests the method that the maximum path avoidance can be applied to the collision avoidance on the extension collision map. Finally, the result proves that multi AUVs effectively navigates to the goal point, avoiding the collision by the suggested method.

• Journal of Information Processing Systems
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• 제16권6호
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• pp.1324-1342
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• 2020

Various modified algorithms of rapidly-exploring random tree (RRT) have been previously proposed. However, compared to the RRT algorithm for collision avoidance with global and static obstacles, it is not easy to find a collision avoidance and local path re-planning algorithm for dynamic obstacles based on the RRT algorithm. In this study, we propose boundary-RRT*, a novel-algorithm that can be applied to aerial vehicles for collision avoidance and path re-planning in a three-dimensional environment. The algorithm not only bounds the configuration space, but it also includes an implicit bias for the bounded configuration space. Therefore, it can create a path with a natural curvature without defining a bias function. Furthermore, the exploring space is reduced to a half-torus by combining it with simple right-of-way rules. When defining the distance as a cost, the proposed algorithm through numerical analysis shows that the standard deviation (σ) approaches 0 as the number of samples per unit time increases and the length of epsilon ε (maximum length of an edge in the tree) decreases. This means that a stable waypoint list can be generated using the proposed algorithm. Therefore, by increasing real-time performance through simple calculation and the boundary of the configuration space, the algorithm proved to be suitable for collision avoidance of aerial vehicles and replanning of local paths.

• 한국군사과학기술학회지
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• 제11권2호
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• pp.53-65
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• 2008

This paper proposes the qualitative method for planning the operation of multi-AUVs with environmental disturbances, which is considered to be a very difficult task. In this paper we use an extension collision map as a collision free motion planner. The tool was originally developed for the multiple ground vehicles with no internal/external disturbance. In order to apply the method to a water environment where there are tides and waves, and currents, we analyze the path deviation error of AUVs caused by external disturbances. And we calculate safety margin for the collision avoidance on the extension collision map. Finally, the simulation result proves that the suggested method in this paper make multi-AUVs navigate to the goal point effectively with no collision among them.

• 대한기계학회논문집A
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• 제24권4호
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• pp.848-857
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• 2000

A pick-and-place operation in 3-dimensional environment is basic operation for human and multi-purpose manipulators. However, there may be a difficult problem for such manipulators. Especially, if the object cannot be moved with a single grasp, regrasping, which can be a time-consuming process, should be carried out. Regrasping, given initial and final pose of the target object, is a construction of sequential transition of object poses that are compatible with two poses in the point of grasp configuration. This paper presents a novel approach for solving regrasp problem. The approach consists of a preprocessing and a planning stage. Preprocessing, which is done only once for a given robot, generates a look-up table which has information of kinematically feasible task space of end-effector through all the workspace. Then, using the table planning automatically determines possible intermediate location, pose and regrasp sequence leading from the pick-up to put-down grasp. Experiments show that the presented is complete in the total workspace. The regrasp planner was combined with existing path.

• 경영정보학연구
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• 제4권2호
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• pp.343-360
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• 2002

IS 프로젝트 성공요인의 하나로서 프로젝트 관리자는 항상 관심의 대상이 되어왔다. 본 연구는 IS 프로젝트 관리자가 갖추어야 될 지식과 기술이 무엇이며, 그러한 기술을 위하여 어떠한 경력개발 경로가 필요한지를 알아보고자 하는 것이다. 프로젝트 관리자에게 필요한 지식과 기술은 기업의 경영전략을 이해하고 IS 전략계획으로 연결하는 능력, 전사적 업무기능을 이해해야 하는 현업 업무력, 새로운 업무를 위한 혁신, 프로젝트 계획과 통제와 같은 일반관리, 의사소통과 리더십과 관련된 인간관계의 관리력, IS 개발에 관련된 기술적 전문성 등의 6 가지로 밝혔다. IS 프로젝트 관리자를 양성하기 위한 경력개발 경로로는 엔지니어, 분석가, 기획가, 프로젝트 리더 등을 거치면서 프로젝트 관리자로 성장하게 되는 모형을 제시하였다. 이러한 연구는 우수한 프로젝트 관리자를 양성하여 IS 프로젝트의 성공 확률을 높이고, 나아가 정보산업의 경쟁력 제고에 도움이 되는 방안을 모색하게 해 줄 것이다.

• 로봇학회논문지
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• 제15권3호
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• pp.277-285
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• 2020

A differential drive wheeled robot is a kind of mobile robot suitable for indoor navigation. Model predictive control is an optimal control technique with various advantages and can achieve excellent performance. One of the main advantages of model predictive control is that it can easily handle constraints. Therefore, it deals with realistic constraints of the mobile robot and achieves admirable performance for trajectory tracking. In addition, the intention of the robot can be properly realized by adjusting the weight of the cost function component. This control technique is applied to the local planner of the navigation component so that the mobile robot can operate in real environment. Using the Robot Operating System (ROS), which has transcendent advantages in robot development, we have ensured that the algorithm works in the simulation and real experiment.

• 대한임베디드공학회논문지
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• 제10권5호
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• pp.317-324
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• 2015

In his paper, we propose the graphic-based direction tracking system that be able to detect the current location and direction of the flight object and virtually run the pointing to the flight direction when a small UAV is located in the occlusion area behind buildings or obstacles in the moving surveillance systems. Based on the experimental results about the simulation flight path extracted from the Mission Planner we found the proposed system operates the desired flight mission effectively in tracking.