• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2012.10a
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• pp.252-254
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• 2012

물류센터내에서는 작업자에 의한 지게차 작업이 주를 이루고 있으나, 점차 물류센터의 대형화, 자동화 및 지능화에 의해 무인지게차에 의한 작업에 관한 연구가 진행되고 있다. 최근 작업 생산성을 높이기 위해, 본 연구진에 의해 이중 포크 (Dual Fork) 장착형 무인지게차에 대한 검토가 이루어지고 있으며, 이중 포크형 무인지게차에 대해서는 새로운 방법의 동적경로할당이 요구된다. 본 연구에서는 4단계 심플한 동적 경로 할당 알고리즘을 제안하였으며, 실제 물류센터에서 유용하게 사용될 수 있도록 하였다. 마지막으로는 시뮬레이션을 통하여 그 유효성을 검증하였다.

• Journal of Navigation and Port Research
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• v.37 no.3
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• pp.309-313
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• 2013

This paper is about a complex sensor system of an automatic guided vehicle(AGV) for loading and unloading payloads. For the AGV to approach to the target rack for loading and unloading the payload, a way to identify the position and orientation was studied. To identify the position and orientation of the AGV accurately, a complex sensor system composed of RFID, IMU, and limit sensors was developed, and the performance of each sensor was undertaken. A model AGV was constructed, and the good performance of the developed complex sensor system was verified through performance experiments.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.05a
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• pp.229-231
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• 2018

As autonomous vehicle technology has been gradually developed, robots that have introduced autonomous navigation systems have been actively involved in areas where there is a lot of livelihoods such as industrial sites and accident sites. For this reason, the unmanned transportation system equipped with the autonomous traveling system is widely used in harmful environments where human access is difficult. In addition, the introduction of the autonomous driving system reduces the collision and casualties that occur in a mobility environment like the industrial field, and it helps the efficient work process. In addition, autonomous driving vehicles can be handled more safely and quickly in a wider area by transmitting the surrounding environment of each vehicle to a server connected to each autonomous driving vehicle and passing it through the main server. In this paper, by utilizing V2X communication for autonomous unmanned forklift system, it can increase industrial workload, reduce loss of life and damage to property through wide area forklifts.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2009.06a
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• pp.575-576
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• 2009

• Journal of Drive and Control
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• v.19 no.4
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• pp.70-76
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• 2022

In this paper, we develops an unmanned test system for the purpose of realizing an actual forklift-based test-bed for the operation durability of the forklift mast. First, two robot actuators were applied to the lever to replace lever manipulation of the operator. For detecting the height of the fork and the tilt angle of the mast, the laser displacement sensor and the inclinometer were installed to the forklift. Next, the embedded control system was used to control the robot actuator with reference to test mode. Experimental evaluation verified that developed test system was effective and practical for the viewpoint of the repeatability of the test mode.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2010.05a
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• pp.743-744
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• 2010

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2011.06a
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• pp.55-56
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• 2011

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.10
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• pp.1051-1058
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• 2011

Unmanned autonomous forklifts have a great potential to enhance the productivity of material handling in various applications because these forklifts can pick up and deliver loads without an operator and any fixed guide. Especially, automation of pallet loading and unloading technique is useful for enhancing performance of logistics and reducing cost for automation system. There are, however, many technical difficulties in developing such forklifts including localization, map building, sensor fusion, control, and so on. This is because the system requires numerous sensors, actuators, and controllers that need to be connected with each other, and the number of connections grows very rapidly as the number of devices grows. This paper presents a vision sensorbased autonomous loading and unloading for network-based unmanned forklift where system components are connected to a shared CAN network. Functions such as image processing and control algorithm are divided into small tasks that are distributed over a number of microcontrollers with a limited computing capacity. And the experimental results show that proposed architecture can be an appropriate choice for autonomous loading in the unmanned forklift.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.10
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• pp.930-935
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• 2015

An unmanned forklift requires precise positioning and pallet detection. Therefore, conventional unmanned forklifts use high-cost sensors to find the exact position of the pallet. In this study, a docking algorithm with two cameras is proposed. The proposed method uses vision data to extract the angle difference between the pallet and the forklift. Then the control law is derived from the extracted angle for successful docking. The extracted angle is compared with the actual angle in the real environment. The control law is tested with the Lyapunov stability test and Routh-Hurwitz stability criterion. Through various experiments, the proposed docking algorithm showed the success rate high enough for real-life applications.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.8
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• pp.1483-1490
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• 2009

This parer is presented multiple path-planning of unmanned autonomous forklift using modified genetic algorithm and fuzzy inference system. There are a task-level feedback method and a method that path is dynamically replaned in realtime while the autonomous vehicles are moving by means of an optimal algorithm for existing multiple path-planning. However, such methods cause malfunctions and inefficiency in the sense of time and energy, and path-planning should be dynamically replanned in realtime. To solve these problems, we propose multiple path-planning using modified genetic algorithm and fuzzy inference system and show the performance with autonomous vehicles. For experiment, we designed and built two autonomous mobile vehicles that equipped with the same driving control part used in actual autonomous forklift, and test the proposed multiple path-planning algorithm. Experimental result that actual autonomous mobile vehicle, we verified that fast optimized path-planning and efficient collision avoidance are possible.