• Journal of Mechanical Science and Technology
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• v.18 no.4
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• pp.630-639
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• 2004

The Stewart platform manipulator is a closed-kinematics chain robot manipulator that is capable of providing high structural rigidity and positional accuracy. However, this is a complex and nonlinear system, so the control performance of the system is not so good. In this paper, a new robust motion control algorithm is proposed. The algorithm uses partial state feedback for a class of nonlinear systems with modeling uncertainties and external disturbances. The major contribution is the design of a robust observer for the state and the perturbation of the Stewart platform, which is combined with a variable structure controller (VSC). The combination of controller and observer provides the robust routine called sliding mode control with sliding perturbation observe. (SMCSPO). The optimal gains of SMCSPO, which is determined by nominal eigenvalues, are easily obtained by genetic algorithm. The proposed fitness function that evaluates the gain optimization is to put sliding function. The control performance of the proposed algorithm is evaluated by the simulation and experiment to apply to the Stewart platform. The results showed high accuracy and good performance.

• The Journal of Korea Robotics Society
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• v.17 no.4
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• pp.417-424
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• 2022

In this paper, the developed trunk cargo unloading automation system is introduced, and the RGB-D sensor-based box loading situation recognition method and unloading plan applied to this system are suggested. First of all, it is necessary to recognize the position of the box in a truck. To do this, we first apply CNN-based YOLO, which can recognize objects in RGB images in real-time. Then, the normal vector of the center of the box is obtained using the depth image to reduce misrecognition in parts other than the box, and the inner wall of the truck in an image is removed. And a method of classifying the layers of the boxes according to the distance using the recognized depth information of the boxes is suggested. Given the coordinates of the boxes on the nearest layer, a method of generating the optimal path to take out the boxes the fastest using this information is introduced. In addition, kinematic analysis is performed to move the conveyor to the position of the box to be taken out of the truck, and kinematic analysis is also performed to control the robot arm that takes out the boxes. Finally, the effectiveness of the developed system and algorithm through a test bed is proved.

• The Journal of Korea Robotics Society
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• v.12 no.2
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• pp.184-193
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• 2017

This work shows how to create an algorithm and implementation for motion and image matching between a vehicle simulator and Unity 3D based virtual object. The motion information of the virtual vehicle is transmitted to the real simulator via a RS232 communication protocol, and the motion is controlled based on the inverse kinematics solution of the platform adopting rotary-type six actuators driving system. Wash-out filters to implement the effective motion of the motion platform are adopted, and thereby reduce the dizziness and increase the realistic sense of motion. Furthermore, the simulator system is successfully designed aiming to reducing size and cost with adaptation of rotary-type six actuators, real driving environment via VR (Virtual Reality), and control schemes which employ a synchronization between 6 motors and 3rd order motion profiles. By providing relatively big sense of motion particularly in impact and straight motions mainly causing simulator sickness, dizziness is remarkably reduced, thereby enhancing the sense of realistic motion.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.20 no.10
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• pp.151-157
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• 2006

As people's living standard is being improved, human works are being replaced by robots. However, because most robots are used in process industry, fixed on the ground, we need to develop human robots that have wide applications. Currently many researches are being conducted on human robots with the object of replacing human works, but because of lack of relevant hardware, such robots are being applied limitedly to very simple tasks. To overcome the limitation, the present study developed a kinematical mechanism and a controller. Based on human kinematics, the shoulders and the arms were composed of master arms with 3 degree of freedom, and we reproduced motions similar to human ones through the characteristics of joint variables and experiment on the trajectory of the end effector.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.12
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• pp.1233-1240
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• 2010

In the flat panel display and semiconductor industries, the visual alignment system is considered as a core technology which determines the productivity of a manufacturing line. It consists of the vision system to extract the centroids of alignment marks and the stage control system to compensate the alignment error. In this paper, we develop a Kalman filter algorithm to estimate the alignment mark postures and propose a coarse-fine alignment control method which utilizes both original fine images and reduced coarse ones in the visual feedback. The error compensation trajectory for the distributed joint servos of the alignment stage is generated in terms of the inverse kinematic solution for the misalignment in task space. In constructing the estimation algorithm, the equation of motion for the alignment marks is given by using the forward kinematics of alignment stage. Secondly, the measurements for the alignment mark centroids are obtained from the reduced images by applying the geometric template matching. As a result, the proposed Kalman filter based coarse-fine alignment control method enables a considerable reduction of alignment time.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.6
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• pp.495-500
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• 2013

This paper proposes a double sliding surfaces based on a sliding mode control for a tracking control of nonholonomic mobile robots in the Cartesian coordinates. In order to remove sliding surface constraints, we design the additional sliding surface for the heading angle with respect to the newly defined coordinates. Then, we define the switching law based on the posture error to combine the designed sliding surface with the previous one. By using the double sliding surfaces and the switching law, we obtain the control law for arbitrary trajectories. It is proved that the position tracking error and the heading direction error asymptotically converge to zero, respectively, with the Lyapunov stability theory. Finally, through computer simulations, we demonstrate the effectiveness of the proposed control system.

• ETRI Journal
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• v.38 no.2
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• pp.337-346
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• 2016

We propose a data-driven kinematic control method for a robotic spatial augmented reality (RSAR) system. We assume a scenario where a robotic device and a projector-camera unit (PCU) are assembled in an ad hoc manner with loose kinematic specifications, which hinders the application of a conventional kinematic control method based on the exact link and joint specifications. In the proposed method, the kinematic relation between a PCU and joints is represented as a set of B-spline surfaces based on sample data rather than analytic or differential equations. The sampling process, which automatically records the values of joint angles and the corresponding external parameters of a PCU, is performed as an off-line process when an RSAR system is installed. In an on-line process, an external parameter of a PCU at a certain joint configuration, which is directly readable from motors, can be computed by evaluating the pre-built B-spline surfaces. We provide details of the proposed method and validate the model through a comparison with an analytic RSAR model with synthetic noises to simulate assembly errors.

• Journal of Biomedical Engineering Research
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• v.24 no.6 s.81
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• pp.495-500
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• 2003

The purpose of this investigation was to study the kinematics of joints between the foot segments based on computer graphic model during the stance? phase of walking. In the model, all joints were assumed to act as monocentric. single degree of freedom hinge joints. The motion of foot was captured by a video collection system using four cameras. The model fitted in an individual subject was simulated with this motion data. The range of motion of the first tarsometatarsal joint was $-8^{\circ}\;\~\;-13^{\circ}$, and the first metatarsophanlangeal joint was $-13^{\circ}\;\~\;-48^{\circ}$. The kinematic data of tarsometatarsal joint and metatarsophanlangeal joint were similar to the previous data. Therefore, our method based on the graphical computer model is considered useful.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.3
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• pp.505-513
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• 2009

Z. Cao had proposed NFRM(new fuzzy reasoning method) which infers in detail using relation matrix. In spite of the small inference rules, it shows good performance than mamdani's fuzzy inference method. But the most of fuzzy systems are difficult to make fuzzy inference rules in the case of MIMO system. The past days, We had proposed the MIMO fuzzy inference which had extended a Z. Cao's fuzzy inference to handle MIMO system. But many times and effort needed to determine the relation matrix elements of MIMO fuzzy inference by heuristic and trial and error method in order to improve inference performances. In this paper, we propose a MIMO fuzzy inference method with the learning ability witch is used a gradient descent method in order to improve the performances. Through the computer simulation studies for the inverse kinematics problem of 2-axis robot, we show that proposed inference method using a gradient descent method has good performances.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.10a
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• pp.175-178
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• 2008

Z. Cao had proposed NFRM(new fuzzy reasoning method) which infers in detail using relation matrix. In spite of the small inference rules, it shows good performance than mamdani's fuzzy inference method. But the most of fuzzy systems are difficult to make fuzzy inference rules in the case of MIMO system. The past days, We had proposed the MIMO fuzzy inference which had extended a Z. Cao's fuzzy inference to handle MIMO system. But many times and effort needed to determine the relation matrix elements of MIMO fuzzy inference by heuristic and trial and error method in order to improve inference performances. In this paper, we propose a MIMO fuzzy inference method with the learning ability witch is used a gradient descent method in order to improve the performances. Through the computer simulation studies for the inverse kinematics problem of 2-axis robot, we show that proposed inference method using a gradient descent method has good performances.