• Proceedings of the Korean Operations and Management Science Society Conference
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• 1995.04a
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• pp.886-890
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• 1995

최근 몇년사이에 산업 전분야에서 로보트의 이용이 증가하고 있는데, 로보트 시스템의 주요목적은 작업영역내에서 작업물을 빠르고 정확하게 다른 장소로 이동시키는 것이다. 이러한 로보트의 이용에 있어서의 어려움 중 하나는 로보트가 목표점으로 움직이는 동안에 작업장내에 있는 장애물, 즉 각종 공구, 시설등의 물체와의 충돌을 피할 수 있도록 프로그램 되어야 하며, 이를 위해서 많은 시간이 소요된다는 것이다. 본 연구에서는 SOM 네트워크를 이용하여 장애물이 존재하는 작업 공간에서 로보트가 장애물과 충돌없이 움직일 수 있는 경로를 구하기 위한 SOM의 응용방안을 소개한다. 본 연구에서는 SOM의 최적 size, 학습계수 요인을 고려하여 2관절 로보트의 충돌회피 경로 발견을 위한 시뮬레이션을 수행하였다.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.39 no.6
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• pp.535-542
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• 2011

The Global Navigation Satellite System(GNSS) is being utilized in numerous applications. The research for autonomous guided vehicles(AGVs) using precise positioning of GNSS is in progress. GNSS based AGVs is useful for setting driving path. This AGV system is more efficient than the previous one. Escipecially, the obstacle is positioned the driving path. Previcious AGVs which follow marker or wires laid out on the road have to stop the front of obstacle. But GNSS based AGVS can continuously drive using obstacle avoidance. In this paper, we developed collision avoidance system for GNSS based AGV using laser scanner and collision avoidance path setting algorithm. And we analyzed the developed system.

• The Journal of the Korea institute of electronic communication sciences
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• v.7 no.1
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• pp.187-194
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• 2012

This paper compares two collision avoidance algorithms using a simulator. The collision avoidance is vital for autonomous navigation of a mobile robot. Artificial potential field method and elastic force method are major approaches for the collision avoidance. The two algorithms are compared in the respect of the time for motion completion and the length of the motion path. The simulator is developed based on IPC(Inter Process Communication) and a differential drive mobile robot is used for the comparison.

• Journal of the Korean Society of Marine Environment & Safety
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• v.24 no.1
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• pp.10-17
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• 2018

To prepare the integrated safety management system 'e-navigation', research is being conducted on the route exchange for sharing intended routes between ship and ship, and between ship and land. But they don't have enough specific grounds for the effects of route exchange and the necessity of its introduction and focus on technical aspects like the implementation of route exchange. This study tried to quantitatively analyze the effects of route exchange on sailing safety with the use of ship handling simulation, integrate simulation performers' subjective evaluations, and investigate the effects of route exchange. The ship-to-ship route exchange resulted in the initial collision avoidance action time was 3.43 minutes faster, the collision avoidance direction change rate was 60 %, the proximity to target A was 31 %, and Mean Rudder Angle Index decreased by 57 %. In addition, 95 % of the survey respondents had an effect on the decision making of collision avoidance, 85 % had a positive impact on safety navigation, 90 % had an accident prevention effect, 70 % reduced the psychological burden of officers, and 70 % should be introduced in practice.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.39 no.6
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• pp.549-559
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• 2015

In this paper, an efficient dynamic reactive motion planning method for an autonomous vehicle in a dynamic environment is proposed. The purpose of the proposed method is to improve the robustness of autonomous robot motion planning capabilities within dynamic, uncertain environments by integrating a virtual plane-based reactive motion planning technique with a sensor fusion-based obstacle detection approach. The dynamic reactive motion planning method assumes a local observer in the virtual plane, which allows the effective transformation of complex dynamic planning problems into simple stationary ones proving the speed and orientation information between the robot and obstacles. In addition, the sensor fusion-based obstacle detection technique allows the pose estimation of moving obstacles using a Kinect sensor and sonar sensors, thus improving the accuracy and robustness of the reactive motion planning approach. The performance of the proposed method was demonstrated through not only simulation studies but also field experiments using multiple moving obstacles in hostile dynamic environments.

• KIPS Transactions on Software and Data Engineering
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• v.11 no.9
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• pp.363-370
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• 2022

Grasping a target object among clutter objects without collision requires machine intelligence. Machine intelligence includes environment recognition, target & obstacle recognition, collision-free path planning, and object grasping intelligence of robot hands. In this work, we implement such system in simulation and hardware to grasp a target object without collision. We use a RGB-D image sensor to recognize the environment and objects. Various path-finding algorithms been implemented and tested to find collision-free paths. Finally for an anthropomorphic robot hand, object grasping intelligence is learned through deep reinforcement learning. In our simulation environment, grasping a target out of five clutter objects, showed an average success rate of 78.8%and a collision rate of 34% without path planning. Whereas our system combined with path planning showed an average success rate of 94% and an average collision rate of 20%. In our hardware environment grasping a target out of three clutter objects showed an average success rate of 30% and a collision rate of 97% without path planning whereas our system combined with path planning showed an average success rate of 90% and an average collision rate of 23%. Our results show that grasping a target object in clutter is feasible with vision intelligence, path planning, and deep RL.

• Journal of the Korea Society of Computer and Information
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• v.18 no.1
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• pp.11-19
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• 2013

For an autonomous multi-mobile robot system, path planning and collision avoidance are important functions used to perform a given task collaboratively and cooperatively. This study considers these important and challenging problems. The proposed approach is based on a potential field method and fuzzy logic system. First, a global path planner selects the paths of the robots that minimize the cost function from each robot to its own target using a potential field. Then, a local path planner modifies the path and orientation from the global planner to avoid collisions with static and dynamic obstacles using a fuzzy logic system. In this paper, each robot independently selects its destination and considers other robots as dynamic obstacles, and there is no need to predict the motion of obstacles. This process continues until the corresponding target of each robot is found. To test this method, an autonomous multi-mobile robot simulator (AMMRS) is developed, and both simulation-based and experimental results are given. The results show that the path planning and collision avoidance strategies are effective and useful for multi-mobile robot systems.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2022.06a
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• pp.133-134
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• 2022

본 논문에서는 자율운항선박의 육상 관제 및 원격제어를 위해, 자율운항선박의 비상상황인식 기술 개발에 대한 기초연구를 수행한다. 자율운항선박 주변의 타선들의 이동 경로를 예측하고 이에 따라 자선의 이동경로와 비교하여, 충돌위험 영역을 식별함으로써 비상상황 인식이 가능하도록 한다. 먼저, 타선의 이동경로 예측을 위해서는 선박자동식별시스템 AIS 정보를 바탕으로, 해당 해역에서의 통항패턴을 분석하고 이를 기반으로 타선의 특정 시간 동안의 이동 경로를 예측한다. 예측된 타선의 이동경로와 함께 자선의 이동경로를 비교 분석함으로, 최근 접점 및 최근접점 거리 정보 기반의 충돌위험영역을 식별한다. 식별된 충돌위험영역의 위험도에 따라 육상 관제센터에서는 원격 제어를 통한 위험상황 회피가 가능하도록 활용할 수 있다. 제안된 방법은 AIS에서 얻어지는 실제 항적 데이터를 이용하여 초기 결과를 검증하였다.

• Journal of IKEEE
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• v.13 no.2
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• pp.150-158
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• 2009

For the autonomous movement, the optimal path planning connecting between current and target positions is essential, and the optimal path of mobile robot means obstacle-free and the shortest length path to a target position. Many actual mobile robots should move without any information of surrounded obstacles. Thus, this paper suggests new methods of path planning and obstacle avoidment, suitable in unknown environments. This method of path planning always tracks the local target expected as the optimal one, and the result of continuous tracking becomes the first generated moving path. This path, however, do not regard the collision with obstacles. Thus, this paper suggests a new method of obstacle avoidance resembled with the Potential Field method. Finally, a simulation confirms the performance and correctness of the path planning and obstacle avoidance, suggested in this paper.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.5
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• pp.592-598
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• 2008

This paper presents collision prediction and avoidance method for AGVS (Automatic Guide Vehicle System). Also, we propose the PO(Right of Path Occupying) with decentralized delay time for collision avoidance. Classified essential element of AGV's working environment is modeled in this paper. Using this model, we propose a new shortest path algorithm using A* search algorithm and obtain the information on AGVs travel time, coordinates and rotation vector. Finally, we use the AGVs information data as input for simulation program. The simulation practice is used in order to evaluate a collision prediction and avoidance, and it has been presented to demonstrate the applicability of the minimize delay time.