• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.5
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• pp.1034-1041
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• 2014

This paper propose a fuzzy inference model for obstacle avoidance for a mobile robot with an active camera, which is intelligently searching the goal location in unknown environments using command fusion, based on situational command using an vision sensor. Instead of using "physical sensor fusion" method which generates the trajectory of a robot based upon the environment model and sensory data. In this paper, "command fusion" method is used to govern the robot motions. The navigation strategy is based on the combination of fuzzy rules tuned for both goal-approach and obstacle-avoidance. We describe experimental results obtained with the proposed method that demonstrate successful navigation using real vision data.

• Proceedings of the Korea Information Processing Society Conference
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• 2019.10a
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• pp.1007-1010
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• 2019

주행 중인 자율주행차의 탑승자는 차량의 거동을 예측할 수 없기 때문에 불안함을 느낄 수 있으므로 차량의 거동 정보를 사전에 탑승자에게 전달하여 심리적 안정을 제공하는 것은 중요하다. 본 논문에서는 완전 자율주행 상황을 가정하여 자율주행 시스템이 발생시키는 주행 의도를 탑승자에게 전달하는 하드웨어 시스템을 제안한다. 제안하는 시스템은 자율주행차량이 사전에 생성된 경로를 따라 주행하면서 출발, 정지, 방향 전환 등과 같은 총 5 가지 상황에 대한 시각, 청각 및 촉각 알림을 통한 자율주행 의도 전달하는 것을 고려한다. 차량용 시트에 모터를 부착하여 촉각 알림을 통해 자율주행 의도를 전달 하였으며, 모니터를 통해 시각 및 청각 알림을 통해 자율주행 의도를 전달하였다. PC 에서 개발에 필요한 시뮬레이션 데이터를 처리하였으며, 시뮬레이션 환경에서 개발, 실험 및 평가가 진행되었다.

• 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.

• Journal of the Korean Society for Precision Engineering
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• v.12 no.1
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• pp.38-47
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• 1995

이 논문에서는 이동로보트가 주행하기 쉬운 경로의 조건을 간단히 보인 후, 이러한 경로를 제작하는 방법을 제시하였다. 과거의 제작방법들은 대체적으로 주어진 점들을 직선으로 연결한 수 모서리를 원호, 클롯호이드 곡선 등으로 모서리 안쪽으로 곡선화하였다. 이 논문에서 제시된 방법은 두 단계로 되어있는데, 먼저 주어진 연속의 점들을 연속의 포우스쳐들로 바꾼 후, 이 포우스쳐들을 클롯호이드 곡선으로 연결한다. 클롯호이드 곡선의 특성상, 생성된 경로는 점선각, 곡률까지 연속적이며 곡률은 구분적으로 선형이며, 이 외에, 과거의 경로는 주어진 점들의 모서리 안쪽을 지나는 것에 비하여, 주어진 점들을 부드럽게 바깥쪽으로부터 통과하는데, 이것은 장애물들이 경로의 모서리의 안쪽에 있는 것을 생각하면 매우 유용한 점이다.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2010.05a
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• pp.87-88
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• 2010

• Journal of Navigation and Port Research
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• v.29 no.8 s.104
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• pp.723-733
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• 2005

This paper presents a deadlock avoidance method for AGVs in automated container terminals. For a more efficient use of AGV traveling area, we divided the area into small-sized grids not enough to cover a whole AGV. Our deadlock avoidance method controls AGVs by identifying strongly connected components(SCCs) in a graph derived from the paths of AGVs on the grids. Also in this paper we suggest a route selection scheme which selects a route by predicting and comparing travel times of candidate routes by using a regression formula. Simulation experiments have shown that the proposed method can control AGVs for 48 hours without deadlocks and the count of AGV visits per QC is increased by $2\~10$ an hour.

• Proceedings of the KIEE Conference
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• 2005.07d
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• pp.2777-2779
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• 2005

최근 로봇 기술의 발전으로 인해 로봇에 관련된 제반 기술에 대한 연구가 활발히 진행되고 있다. 이러한 연구 중의 하나가 이동 로봇이 스스로 장애물을 감시하여 회피하도록 적절한 이동 경로를 생성해주는 연구이다. 따라서 본 논문에서는 이동 경로 상에 존재하는 장애물을 회피하기 위한 방법으로 비전 시스템에 기반하여 주행 거리 및 주행 시간을 최소화하여 목표점에 도달한 수 있도록 장애물을 회피하는 방법에 대하여 연구하였다. 시뮬레이션을 통해 제안한 방법의 성능을 검증하여보았다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.9
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• pp.1987-1992
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• 2010

This paper deals with the method of using the three dimensional characteristic information to classify the front environment in travelling by using the images captured by a CCD camera equipped on a mobile robot. The images detected by the three dimensional characteristic information is divided into the part of obstacles, the part of corners, and th part of doorways in a corridor. In designing the travelling path of a mobile robot, these three situations are used as an important information in the obstacle avoidance and optimal path computing. So, this paper proposes the method of deciding the travelling direction of a mobile robot with using input images based upon the suggested algorithm by preprocessing, and verified the validity of the image information which are detected as obstacles by the analysis through neural network.

• Journal of Korean Society for Geospatial Information Science
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• v.22 no.3
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• pp.79-85
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• 2014

For the successful operation of unmanned ground vehicles(UGVs), optimal path planning should be considered with trafficability analysis, threat analysis, and so on. From among these, trafficability analysis is immensely important for safeness of UGVs especially in the case of driving the off-road such as unpaved road, grassland, and open fields. Geographical information has a pivotal role in extracting data and measuring cost for specified regions of interest. In this paper, we review possibilities to apply Land Cover Map(LCM) as a new, fundamental source and propose a new generation method of trafficability analysis map for optimal path planning of UGV. The simulation results show that the proposed method significantly improve the previous method by applying LCM either alone or in combination with the other GIS.

• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.5
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• pp.699-705
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• 2009

This paper is represented to research of driving control for the forklift AGV. The related works that were studied about AGV as heavy equipment used two methods which are magnet-gyro and wire guidance for localization. However, they have weaknesses that are high cost, difficult maintenance according to change of environment. In this paper, we develop localization system through sensor fusion with laser navigation system and encoder, gyro for robustness. Also we design driving controller using fuzzy and proportional control. It considers distance and angle difference between forklift AGV and pallet for engaging work. To analyze performance of the proposed control system, we experiment in same working condition over 10 times. In the results, the average error was presented with 54.16mm between simulation of control navigation and real control navigation. Consequently, experimental result shows that the performance of proposed control system is effective.