• 한국생산제조학회지
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• 제25권2호
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• pp.112-117
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• 2016

In the construction industry, concrete polishing is used to grind and rub the surface of concrete grounds with polishing machines to increase the strength of the concrete after deposition. Polishing is performed manually in spite of the generation of dust and the requirement of frequent replacements of the polishing pad. The concrete polishing robot developed in this research is a novel polishing automation system for preventing the workers from being exposed to poor working environments. This robot is able to change multiple polishing tools automatically; however, the workers can conveniently replace the worn-out polishing pads with new ones. The mobile platform of the polishing robot employs omnidirectional wheels to enable a flexible motion even in small and complicated workspaces. To evaluate the performance of the developed concrete polishing robot, extensive experiments including square trajectory tracking, automatic tool changing, actual polishing, and path generation simulation were performed.

• 한국생산제조학회지
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• 제23권5호
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• pp.485-497
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• 2014

This paper presents the robot vision control schemes based on the Newton-Raphson (N-R) and the Extended Kalman Filter (EKF) methods for the tracking of moving targets. The vision system model used in this study involves the six camera parameters. The difference is that refers to the uncertainty of the camera's orientation and focal length, and refers to the unknown relative position between the camera and the robot. Both N-R and EKF methods are employed towards the estimation of the six camera parameters. Based on the these six parameters estimated using three cameras, the robot's joint angles are computed with respect to the moving targets, using both N-R and EKF methods. The two robot vision control schemes are tested by tracking the moving target experimentally. Given the experimental results, the two robot control schemes are compared in order to evaluate their strengths and weaknesses.

• 한국기계가공학회지
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• 제18권8호
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• pp.104-109
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• 2019

Damage caused by wild animals such as pheasants and magpies is a problem in rural areas. A bird repellent system based on sensing and repelling farm pest animals and birds is proposed herein. This system is equipped with a bird model part on a supporting platform and comprises a sound source generator, a system control user interface, and a sensor in the center. The sensor is composed of an illuminance sensor and a PIR sensor. The illuminance sensor distinguishes between day and night, whereas the PIR sensor detects birds or wild animals and outputs them from the sound generator. The entire system can be managed easily by the user interface and system control.

• 한국기계가공학회지
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• 제17권5호
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• pp.161-172
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• 2018

This paper proposed the robot vision control method to track a moving rigid body target using the vision system model that can actively control camera parameters even if the relative position between the camera and the robot and the focal length and posture of the camera change. The proposed robotic vision control scheme uses a batch method that uses all the vision data acquired from each moving point of the robot. To process all acquired data, this robot vision control scheme is divided into two cases. One is to give an equal weight for all acquired data, the other is to give weighting for the recent data acquired near the target. Finally, using the two proposed robot vision control schemes, experiments were performed to estimate the positions of a moving rigid body target whose spatial positions are unknown but only the vision data values are known. The efficiency of each control scheme is evaluated by comparing the accuracy through the experimental results of each control scheme.

• 한국산업융합학회 논문집
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• 제22권2호
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• pp.209-218
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• 2019

This study proposes a new approach to Control the Orientation and position based on obstacle avoidance technology by multi sensors fusion and autonomous travelling control of mobile robot system for implimentation of Smart FA. The important focus is to control mobile robot based on by the multiple sensor module for autonomous travelling and obstacle avoidance of proposed mobile robot system, and the multiple sensor module is consit with sonar sensors, psd sensors, color recognition sensors, and position recognition sensors. Especially, it is proposed two points for the real time implementation of autonomous travelling control of mobile robot in limited manufacturing environments. One is on the development of the travelling trajectory control algorithm which obtain accurate and fast in considering any constraints. such as uncertain nonlinear dynamic effects. The other is on the real time implementation of obstacle avoidance and autonomous travelling control of mobile robot based on multiple sensors. The reliability of this study has been illustrated by the computer simulation and experiments for autonomous travelling control and obstacle avoidance.

• 한국공작기계학회:학술대회논문집
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• 한국공작기계학회 2003년도 추계학술대회
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• pp.207-212
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• 2003

This paper proposed trajectory tracking control of Mobile Robot. Trajectory tracking control scheme are Real coding Genetic-Algorithm and Back-propergation Algorithm. Control scheme ability experience proposed simulation.

• 한국공작기계학회:학술대회논문집
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• 한국공작기계학회 2004년도 추계학술대회 논문집
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• pp.181-186
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• 2004

This paper proposed trajectory tracking control of Mobile Robot. Trajectory tracking control scheme are Real coding Genetic-Algorithm and Back-propergation Algorithm. Control scheme ability experience proposed simulation.

• 한국생산제조학회지
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• 제6권1호
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• pp.7-17
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• 1997

During the past decade, there were many well-established theories for the adaptive control of linear systems, but there exists relatively little general theory for the adaptive control of nonlinear systems. Adaptive control technique is essential for providing a stable and robust performance for application of industrial robot control. Neural network computing methods provide one approach to the development of adaptive and learning behavior in robotic system for manufacturing. Computational neural networks have been demonstrated which exhibit capabilities for supervised learning, matching, and generalization for problems on an experimental scale. Supervised learning could improve the efficiency of training and development of robotic systems. In this paper, a new scheme of adaptive-neuro control system to implement real-time control of robot manipulator using digital signal processors is proposed. Digital signal processors, DSPs, are micro-processors that are developed particularly for fast numerical computations involving sums and products of variables. The proposed neuro control algorithm is one of learning a model based error back-propagation scheme using Lyapunov stability analysis method. The proposed adaptive-neuro control scheme is illustrated to be an efficient control scheme for implementation of real-time control for SCARA robot with four-axes by experiment.

• 한국기계가공학회지
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• 제18권5호
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• pp.23-28
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• 2019

In recent years, medium- to large-scale transportation machinery and machine tool manufacturing process lines have shown a trend toward centralization, softening, lightening, and slimming to reduce costs and increase productivity. This has increased the demand for vertical articulated robots. When developing and introducing a heavy weight-handling robot that can be easily applied to existing production lines, it is expected to have a great effect in securing industrial competitiveness by solving industrial issues such as the decreased productivity and increased risk of accidents due to work involving heavy lifting. In this study, we design a 6-axis robot mechanism with a heavy load-handling capacity of 700kg or more for large-sized materials of various types supplied in small quantities.

• 한국생산제조학회지
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• 제7권1호
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• pp.104-111
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• 1998

This study solves the inverse kinematics problem of industrial FANUC robot. Because every joint angle of FANUC robot is dependent on the position of end-effector and the direction of approach vector, arm metrix T6 is very complicated and each joint angle is a function of other joint angles. Therefore, the inverse kinematics problem can not be solved by conventional methods. Noticing the fact that if one joint angle is known, the other joint angles are calculated by the algebraic methods. $ heta$1 is calculated using neumerical analysis method, and solves inverse kinematics problem. This proposed method, in this study, is more simpler and faster than conventional methods and is very useful in the real-time control of the manipulator.