• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1603-1608
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• 2003

Multiple robotics systems with several sub-chains have a characteristic that grasp a common object with internal loading not to loose the grip. The investigation for the internal loading of a triple manipulator has been few as compared to a dual manipulator. In this paper, type of the internal loading for a triple manipulator system is investigated through analysis of the null space of the system. Several types of the internal loading are shown for general planar and spatial type triple robots, which rigidly grasp the common object. The general scheme is applied to analysis of the internal loading for the three-fingered and three-legged robots having a point contact with the grasped object.

• The Journal of Korea Robotics Society
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• v.17 no.3
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• pp.288-295
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• 2022

This study shows a system identification method of a balancing loading device for a stair climbing delivery robot. The balancing loading device is designed as a 2-axes gimbal structure and is interpreted as two independent pendulum structures for simplifying. The loading device's properties such as mass, moment of inertia, and position of the center of gravity are changeable for luggage. The system identification process of the loading device is required, and the controller should be optimized for the system in real-time. In this study, the system identification method is based on least squares method to estimate the unknown parameters of the loading device's dynamic equation. It estimates the unknown parameters by calculating them that minimize the error function between the real system's motion and the estimated system's motion. This study improves the accuracy of parameter estimation using a null space solution. The null space solution can produce the correct parameters by adjusting the parameter's relative sizes. The proposed system identification method is verified by the simulation to determine how close the estimated unknown parameters are to the real parameters.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.281-286
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• 2005

The main objective of the research work presented in this article is to present a systematic approach for designing a multilayer feed-forward artificial neural network based self-tuning power system stabilizer (ST-ANNPSS). In order to suggest an approach for selecting the number of neurons in the hidden layer, the dynamic performance of the system with ST-ANNPSS is studied and hence compared with that of conventional PSS. Finally the effect of variation of loading condition and equivalent reactance, Xe is investigated on dynamic performance of the system with ST-ANNPSS. Investigations reveal that ANN with one hidden layer comprising nine neurons is adequate and sufficient for ST-ANNPSS. Studies show that the dynamic performance of STANNPSS is quite superior to that of conventional PSS for the loading condition different from the nominal. Also it is revealed that the performance of ST-ANNPSS is quite robust to a wide variation in loading condition.

• International Journal of Internet, Broadcasting and Communication
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• v.14 no.1
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• pp.85-94
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• 2022

Recently, consumers who prefer contactless consumption are increasing due to pandemic trends such as Corona 19. This is the driving force for developing the last mile-based logistics ecosystem centered on the online e-commerce market. Lastmile led to the continued development of the logistics industry, but increased the amount of cargo in urban area, and caused social problems such as overcrowding of logistics. The courier service in the logistics base area utilizes the process of visiting the delivery site directly because the courier must precede the loading work of the cargo in the truck for the delivery of the ordered product. Currently, it's carried out as automated logistics equipment such as conveyor belt in unloading or classification stage, but the automation system isn't applied, so the work efficiency is decreasing and the intensity of the courier worker's labor is increased. In particular, small-scale courier workers belonging to the sub-terminal unload at night at underdeveloped facilities outside the city center. Therefore, the productivity of the work is lowered and the risk of safety accidents is exposed, so robot-based loading technology is needed. In this paper, we have derived the top-level concept and requirements of robot-based loading system to increase the flexibility of logistics processing and to ensure the safety of courier drivers. We defined algorithms and motion concepts to increase the cargo loading efficiency of logistics sub-terminals through the requirements of end effector technology, which is important among concepts. Finally, the control technique was proposed to determine and position the load for design input development of the automatic conveyor system.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.9
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• pp.816-821
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• 2005

The remote operation of $4\~5$ cranes for container loading/unloading at a port by one operator will dramatically improve loading/unloading efficiency through productivity increase, cost reduction, and so on. This study develops a remote crane control system for container loading/unloading yard cranes. First, a wireless video and audio system to transmit views and sounds of the working field is designed by using 3 web cameras and a microphone. Next, a RSVP-based multi-path reservation method is presented with a view to improving the quality of service in the communication network for remote control. Simulation results show that a RSVP-based multi-path reservation can enhance the reservation success rate in the TCP/IP network.

• 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.11 no.2
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• pp.103-108
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• 2005

Loading/Unloading task in the real industry is performed by crane, but most of the loading/unloading task with the weight of 5kg∼30kg is done by human workers and this kind of work causes industrial disaster of workers. Therefore it is necessary to develop low cost loading/unloading manipulator system to prevent this kind of industrial accidents. This paper is concerned with the design and fabrication of 2 axis pneumatic manipulators using on/off solenoid valves and accurate position control without respect to the external load and low damping in the pneumatic rotary actuator. To overcome the change of external load, switching of control parameter using LVQNN (Learning Vector Quantization Neural Network) is newly applied, which estimates the external loads in the pneumatic cylinder. As an underlying controller, a state feedback controller using position, velocity and acceleration is applied to the switching control system. The effectiveness of the proposed control algorithms are demonstrated through experiments of pneumatic cylinder with various loads.

• Journal of Institute of Control, Robotics and Systems
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• v.12 no.7
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• pp.713-718
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• 2006

Supersonic jet fighter aircraft have several different weapon loading configuration to support air-to-air combat and air-to-ground delivery of weapon modes. Especially, asymmetric loading configurations could result in decreased handling qualities for the pilot maneuvering of the aircraft. The design of the T-50 lateral-directional roll axis control laws change from beta-betadot feedback structure to simple roll rate feedback structure and gains such as F-16 in order to improve roll-off phenomena during pitch maneuver in asymmetric loading configuration. Consequently, it is found that the improved control law decreases the roll-off phenomenon in lateral axes during pitch maneuver, but initial roll response is very fast and wing pitching moment is increased. In this paper, we propose the lateral control law blending between beta-betadot and simple roll rate feedback system in order to decreases the roll-off phenomenon in lateral axes during pitch maneuver without degrading of roll performance.

• The Journal of Korea Robotics Society
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• v.19 no.1
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• pp.79-91
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• 2024

Large warehouses are building automation systems to increase efficiency. However, small warehouses, military bases, and local stores are unable to introduce automated logistics systems due to lack of space and budget, and are handling tasks manually, failing to improve efficiency. To solve this problem, this study designed small loading and unloading equipment that can be mounted on transportation vehicles. The equipment can be controlled remotely and is automatically controlled from the point where pallets loaded with cargo are visible using real-time video from an attached camera. Cargo recognition and control command generation for automatic control are achieved through a newly designed deep learning model. This model is designed to be optimized for loading and unloading equipment and mission environments based on the YOLOv3 structure. The trained model recognized 10 types of palettes with different shapes and colors with an average accuracy of 100% and estimated the state with an accuracy of 99.47%. In addition, control commands were created to insert forks into pallets without failure in 14 scenarios assuming actual loading and unloading situations.

• ICROS
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• v.7 no.6
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• pp.10-17
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• 2001

본 논문에서는 훈련용과 연구용 시뮬레이터들에서 차량조종 및 자동조종(autopilot) 시스템들을 시뮬레이션하기 위하여 공통적으로 사용되는 기술들을 소개한다. 여기서 언급하는 차량 조종 시스템들은 고정익기와 회전익기의 비행제어시스템은 물론 지상차량의 조종 시스템들을 모두 포함한다. 본 논문은 다양한 유형의 비행 및 지상차량 조종 시스템들에 대한 검토로 시작된다. 다음으로 차량조종 및 자동조종 시스템들의 시뮬레이션과 모델링, 조정 부하(control loading)라 통상 일컫는 조종감(control feel)의 시뮬레이션, 조종계통 모델링툴 시스템 통함 및 시스템 성능 비준 등의 주요 주제들이 이어진다.