The role of QR Code robots in smart logistics is great. Cognitive robots, such as logistics robots, were mostly used to adjust routes and search for peripheral sensors, cameras, and recognition signs attached to walls. However, recently, the ease of making QR Codes and the convenience of producing and attaching a lot of information within QR Codes have been raised, and many of these reasons have made QR Codes recognizable as visions and others. In addition, there have been cases in developed countries and Korea that control several of these robots at the same time and operate logistics factories smartly. This representative case is the KIVA robot in Amazon. KIVA robots are only operated inside Amazon, but information about them is not exposed to the outside world, so a variety of similar robots are developed and operated in several places around the world. They are applied in various fields such as education, medical, silver, military, parking, construction, marine, and agriculture, creating a variety of application robots. In this work, we are developing a robot that can recognize its current position, move and control in the directed direction through two-dimensional QR Codes with the same horizontal and vertical sides, and the error is to create a QR Code robot with accuracy to reach within 3mm. This paper focuses a study on the application of QR Code position recognition during the development of QR Code-aware indoor mobility robots.

The role of QR Code robots in smart logistics is great. Cognitive robots, such as logistics robots, were mostly used to adjust routes and search for peripheral sensors, cameras, and recognition signs attached to walls. However, recently, the ease of making QR Codes and the convenience of producing and attaching a lot of information within QR Codes have been raised, and many of these reasons have made QR Codes recognizable as visions and others. In addition, there have been cases in developed countries and Korea that control several of these robots at the same time and operate logistics factories smartly. This representative case is the KIVA robot in Amazon. KIVA robots are only operated inside Amazon, but information about them is not exposed to the outside world, so a variety of similar robots are developed and operated in several places around the world. They are applied in various fields such as education, medical, silver, military, parking, construction, marine, and agriculture, creating a variety of application robots. In this work, we are developing a robot that can recognize its current position, move and control in the directed direction through two-dimensional QR Codes with the same horizontal and vertical sides, and the error is to create a QR Code robot with accuracy to reach within 3mm. This paper focuses a study on the application of QR Code recognition system during the development of QR Code-aware indoor mobility robots.

The role of QR Code robots in smart logistics is great. Cognitive robots, such as logistics robots, were mostly used to adjust routes and search for peripheral sensors, cameras, and recognition signs attached to walls. However, recently, the ease of making QR Codes and the convenience of producing and attaching a lot of information within QR Codes have been raised, and many of these reasons have made QR Codes recognizable as visions and others. In addition, there have been cases in developed countries and Korea that control several of these robots at the same time and operate logistics factories smartly. This representative case is the KIVA robot in Amazon. KIVA robots are only operated inside Amazon, but information about them is not exposed to the outside world, so a variety of similar robots are developed and operated in several places around the world. They are applied in various fields such as education, medical, silver, military, parking, construction, marine, and agriculture, creating a variety of application robots. In this work, we are developing a robot that can recognize its current position, move and control in the directed direction through two-dimensional QR Codes with the same horizontal and vertical sides, and the error is to create a QR Code robot with accuracy to reach within 3mm. This paper focuses a study on the position recognition control using QR Code during the development of QR Code-aware indoor mobility robots.

Since the encoder and resolver are expensive, it is difficult to apply it as a position sensor of a motor in a real industrial field. Optical position sensors, such as encoders and resolvers, are also difficult to mount because of their size and durability. Therefore, in order to solve these problems, we propose a system that uses a linear motor as a stator and a magnet plate as a mover, and a system that excludes a separate linear scale and uses two linear Hall sensors and permanent magnets to generate a conventional sine wave, A linear motor capable of detecting an absolute position and a movement position of a magnet, a control method thereof, and a technology development that can reduce a production cost by developing a position control system using a magnet mover that can improve stability and reliability.

The purpose of this study is to design and control position and torque based on the steering controller of power tiller simulator developed by the National Institute of Agricultural Sciences. The tiller simulator selects sensors and motors to detect the motion of the mechanism required for steering, and controls the tiller's steering controller through the PID control method and the PWM control method which can control simultaneously the position and torque. Simulation tests are carried out under various conditions to verify the efficiency of the proposed controller. The power tiller training simulator can be used as a means to prevent agricultural machinery accidents caused by human factors. Through the simulator, the driver can experience a variety of tasks without any risk of collision, the results of his actions, and learn the cause and effect concepts, which can be used for safety education and accident experience.

Recently, a study on reducing the weight of the robot arm, which enables a high-speed operation and enables reducing the energy consumption has been actively carried out. A lightweight robot arm is hard to control because it behaves like a flexible body rather than a rigid body. This paper proposes a controller which combines a PID controller and a fuzzy logic controller for control the position and vibration of the flexible robot arm. In order to show the effectiveness of the proposed controller, MSC.ADAMS computational model which incorporates the finite element flexible robot arm model is developed, and is used for performing simulations. Simulations are carried out with two reference inputs, and three end masses. Simulation results show that the proposed controller controls the position and vibration of the flexible robot arm adaptively without being affected by the reference input and the end mass.

Paddy harrow machine used hydraulic actuator system has been changed to the electric actuator system method. Because driving system of the agricultural equipments has been changed to electric power system. Besides, the effort to reduce the tractor machine's horse power is proceeding rapidly. In this paper, pressure, load scale factor and loading force(dynamic, static force) are considered to determine the cylinder diameter of the electric actuator. The algorithms of paddy harrow machine was studied to control and test the components of link by using the PLC diagram. Also, the electric actuator mechanism system was evaluated through the PLC algorithm. These test results can be attributed to select the actuator capacity and to determine the reliability of the electric actuator system

The objective of this study was to evaluate the effective inoculation position of Neoseiulus californicus for control of Tetranychus urticae on apple branch. This study was conducted under green house conditions. N. californicus was inoculated at different position (Top, Middle and Bottom) of apple branch with a 20:1 ratio (T. urticae:N. californicus). Overall, N. californicus significantly reduced T. urticae numbers in the treatment branches than in the control branch. At 10th day, the T. urticae population was most significantly reduced in the treatment ‘Top’ in which N. californicus were inoculated on the leaf positioned in the top of a branch than in other treatments. At 20th day, most of T. urticae were exterminated in all treatment branches. The daily movement of N. californicus and T. urticae,and their coexistence on apple branch was monitored. Adult N. californicus disappeared from the branch as soon as T. urticae were exterminated in the treatment branches. The result indicates that N. californicus disperse downwards more than upwards in the tree, and the most effective inoculation position for N. californicus for control of T. urticae is the leaves positioned in the top of a branch.

Generally, the three position solenoid valve has veen used for the hydraulic steering gear on account of it’s low cost, simplicity in device, etc. But, there is some off-set because of dead-zone which exists in on-off valves. In this paper, we proposed a combined controller which was added an integral controller to an only on-off one in hydraulic steering gear control system used low speed three position solenoid valve. Experimental results show that the off-set is removed, and the number of valve switching is reduced considerable. The validity of proposed method comparing with an only on-off control was proved by the response experiments.

The DC Servo Motor has been used as an actuator in automatic control fields because of the good response and the control easiness nevertheless it has some disadvantage such as spark at the brush. Recently, along with the fast development of semiconductor industries, the digital control scheme is increasing in comparison with analog control because of the strength against noise and the accuracy. In this paper, authors proposed a combined control algorithm, which is mixed Modified Minimum Time Position Control(MMTPC) and PI control algorithm. for minimum time position control of DC Servo Motor by the one-chip microcontroller. The proposed control algorithm showed the fast response and offset-free. The validity of the proposed method comparing with the VSS control is proved by the response experiments.

Analog PID controllers have been designed to make good use of position control in industries. Recently, the importance of digital position control is emphasized for the requirements of controller which are not only to control the objects but to include various aspects such as easiness of design and implementation, simple exchange of control program and convenient communications of data between various controllers and a host computer. This study proposes a combined control method which is mixed the vaiable structure control (VSC) with the PI control for minimum time position control of DC servo motor by microcomputer. The results of test by this method show offset-free and minimum time optimal position control which is not affected by the disturbance and the system parameter variations. The validity of the proposed method comparing with the conventional PID control is proved by the response experiments.

The Variable Structure System(VSS) will be of much intrest to educators and design engineers who wish to demonstrate and investigate sophisticated position control methods and their applications. This paper describes DC motor position control by means of VSS concept. The control scheme is derived, implemented and tested in the laboratory where IBM AT computer has been used as a digital controller to control a representative servo system. The control system schematic is given and sample results are shown for illustration. This experiment may serve as a basis for further application of VSS.

본 논문에서는 수중운동체 중 하나인 잠수함의 코닝타워(Conning tower) 위치 및 제어판 형태에 따라 4가지 타입별로 나누어 회 전팔 시험(Rotating arm test)을 실시하였다. 또한 본 RA 시험을 통하여 유체력 미계수를 추정하였으며 수평면 운동에 대한 동적 안정성 (Dynamic stability)을 평가하였다. 특히, 자유수면의 영향으로부터 자유로운 심도비(Depth ratio) 6.0에서 힘과 모멘트를 측정한 후, 다중회귀 분석을 이용하여 유체력 미계수를 추정하였다. 최종적으로 선형유체력 미계수를 이용한 수평면 동적 안정성 지수를 산정함으로써 잠수함 타 입별 특성이 동적 안정성에 미치는 영향을 분석하였다.

In the offshore crane system, the requirements on the operating safety are extremely high due to many external factors. Rope extension is one of the factors producing vertical vibration of load. In this study, the load is carried by the motor-winch actuator control and the rope is modeled as a mass-damper-spring system. To control the load position and suppress the vertical vibration of the load, a control system based on input-output linearization method is proposed. By the simulation and experiment results with pilot crane model, the effectiveness of proposed control method is evaluated and verified.

본 연구에서는 통증제어가 거의 불가능한 급성요통 환자를 대상으로 바로 누운 자세를 할 수 없는 환자에게 불가피하게 자기공명검사를 받아야할 환자를 위해 기존촬영방법인 정상 체위 바로 누운 자세 대신 변형된 옆으로 누운 자세를 취하게 하여 기존 척추 전용 코일과 복부 전용 코일을 이용하여 요통을 경감시키고 불안정한 자세 보정과 움직임에 의한 인공물을 줄여 장시간 검사를 받는 환자에게 피로감을 감소시켜 자기공명검사의 성공률을 높이고자 한다. 평가방법으로는 영상의 질을 정성적 평가로 하였으며 결과로는 정상인 연구대상자 기존촬영방법인 바로 누운 자세의 평균 점수는 4.64점, 정상인 연구대상자 옆으로 누운 자세(A군)는 3.44점, 극심한 요통을 호소하는 비정상인 연구대상자 옆으로 누운 자세(B군)는 3.40점으로 나타났다. 결론적으로 정상인 연구대상자의 기존촬영방법인 바로 누운 자세에서 검사한 정성적인 평가는 예상대로 높게 나타났으나 정상인 연구대상자 옆으로 누운 자세와 극심한 요통을 호소하는 비정상인 연구대상자 옆으로 누운 자세로 검사한 영상의 정성적 평가는 거의 비슷하게 나타났다. 또한 극심한 요통을 호소하는 비정상인 연구대상자 옆으로 누운 자세(B군)의 영상평가에서 영상의학과 전문의의 영상판독에도 문제가 없는 것으로 나타났다. 이에 바로 누운 자세에서 검사를 진행함에 불편을 겪는 환자에게 이러한 기법이 보편화 된다면 임상에서 많이 활용될 것으로 사료된다.

Control of a robot manipulator in contact with the environment is usually conducted by the direct feedback control using a force-torque sensor or the indirect impedance control. In these methods, however, the control algorithms become complicated and the performance of position and force control cannot be improved because of the mechanical properties of the passive components. To cope with such problems, redundant actuation has been used to enhance the performance of position control and force control. In this research, a Double Actuator Unit (DAU) is proposed, with which the force control algorithm can be simplified and can make the robot ensure the safety during the external collision. The DAU is composed of two actuators; one controls the position and the other modulates the joint stiffness. Using this unit, it is possible to independently control the position and stiffness. The DAU based on the planetary gears is investigated in this paper. Performance using the DAU is also verified by various experiments. It is shown that the manipulator using this mechanism provides better safety during the impact with the environment by reducing the joint stiffness appropriately on detecting the collision of a manipulator.

본 논문에서는 항만 자동화를 위해 새로이 제안된 리니어 모터 기반 컨테이너 이송시스템에 지능제어기법을 이용하여 그 정밀도를 향상시키고자 한다. LMCTS(Linear Motor-based Container Transfer System)는 스케일의 거대함 때문에 일반 리니어 모터에서 중요시 되지 않는 정지마찰력과 디텐트럭(detent force)이 정밀제어에 큰 문제가 된다. 특히, 컨테이너 적제유무에 따라 시스템 자체가 급격히 변하므로 기존의 PID형 제어기로는 좋은 성능을 얻기 어렵다. 따라서 본 논문에서는 같은 구조를 갖는 두 개의 DR-FNN(Dynamically- constructed Recurrent Fuzzy Neural Network)를 제어기와 에뮬레이터로 구성하여 이러한 문제를 해결하고자 하였다.

This research aims to seek active control of ball-beam position stability by resorting to neural networks whose layers are given bias weights. The controller consists of an LQR (linear quadratic regulator) controller and a neural networks controller in parallel. The latter is used to improve the responses of the established LQR control system, especially when controlling the system with nonlinear factors or modelling errors. For the learning of this control system, the feedback-error learning algorithm is utilized here. While the neural networks controller learns repetitive trajectories on line, feedback errors are back-propagated through neural networks. Convergence is made when the neural networks controller reversely learns and controls the plant. The goals of teaming are to expand the working range of the adaptive control system and to bridge errors owing to nonlinearity by adjusting parameters against the external disturbances and change of the nonlinear plant. The motion equation of the ball-beam system is derived from Newton's law. As the system is strongly nonlinear, lots of researchers have depended on classical systems to control it. Its applications of position control are seen in planes, ships, automobiles and so on. However, the research based on artificial control is quite recent. The current paper compares and analyzes simulation results by way of the LQR controller and the neural network controller in order to prove the efficiency of the neural networks control algorithm against any nonlinear system.

In this paper, applications of multilayer neural networks to control of flexible robot beam are considered. The multilayer nerual networks can be used to approximate any continuous function to a desired degree of accuracy and the weights are updated by Gradient Method. When a flexible beam is rotated by a motor through the fixed end, transverse vibration may occur. The motor torque should be controlled insuch a way that the motor rotates by a specified angle, while simultaneously stabilizing vibration of the flexible manipulators so that is arrested as soon as possbile at the end of rotation. Accurate control of lightweight beam during the large changes in configuration common to robotic tasks requires dynamic models that describe both rigid body motions, as well as the flexural vibrations. Therefore, a linear dynamic state-space model of for a single link flexible robot beam is derived and PD controller, LQP controller, and inverse dynamical neural networks controller are composed. The effectiveness the proposed control system is confirmed by computer simulation.