• Journal of the Korea Institute of Building Construction
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• v.23 no.2
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• pp.209-220
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• 2023

Ensuring accuracy within tolerance is crucial for a marking robot; however, rebar displacement frequently occurs during the structural work process, necessitating corrections to layout lines or rebar locations. To guarantee precision and automation, the marking robot must be capable of measuring rebar error and determining appropriate adjustments for marking lines and rebar placement. Consequently, this study proposes a method for measuring rebar location error using a LiDAR sensor and implementing a layout assessment process based on the measurement results. The rebar recognition experiment using the LiDAR sensor yielded an average error of 5mm, demonstrating a reliable level of accuracy for wall rebars. Additionally, this research proposed a process that enables the robot to evaluate rebar and marking corrections based on the error range. The findings of this study can contribute to the automated operation of marking robots while accounting for construction errors, potentially leading to improvements in structural quality.

• Journal of Institute of Control, Robotics and Systems
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• v.12 no.1
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• pp.41-46
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• 2006

Ubiquitous location based services, offer helpful services anytime and anywhere by using real-time location information of objects based on ubiquitous network. Particularly, autonomous mobile robots can be a solution for various applications related to ubiquitous location based services, e.g. in hospitals, for cleaning, at airports or railway stations. However, a meaningful and still unsolved problem for most applications is to develop a robust and cheap positioning system. A typical example of position measurements is dead reckoning that is well known for providing a good short-term accuracy, being inexpensive and allowing very high sampling rates. However, the measurement always has some accumulated errors because the fundamental idea of dead reckoning is the integration of incremental motion information over time. The other hand, a localization system using RFID offers absolute position of robots regardless of elapsed time. We construct an absolute positioning system based on RFID and investigate how localization technique can be enhanced by RFID through experiment to measure the location of a mobile robot. Tags are placed on the floor at 5cm intervals in the shape of square in an arbitrary space and the accuracy of position measurement is investigated . To reduce the error and the variation of error, a weighting function based on Gaussian function is used. Different weighting values are applied to position data of tags since weighting values follow Gaussian function.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.8
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• pp.744-749
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• 2012

In this paper, we suggest that how to improve an accuracy of mobile robot's localization by using the sensor network information which fuses the machine vision camera, encoder and IMU sensor. The heading value of IMU sensor is measured using terrestrial magnetism sensor which is based on magnetic field. However, this sensor is constantly affected by its surrounding environment. So, we isolated template of ceiling using vision camera to increase the sensor's accuracy when we use IMU sensor; we measured the angles by pattern matching algorithm; and to calibrate IMU sensor, we compared the obtained values with IMU sensor values and the offset value. The values that were used to obtain information on the robot's position which were of Encoder, IMU sensor, angle sensor of vision camera are transferred to the Host PC by wireless network. Then, the Host PC estimates the location of robot using all these values. As a result, we were able to get more accurate information on estimated positions than when using IMU sensor calibration solely.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.532-535
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• 2022

Path following algorithms have been intensively studied for various mobile platforms such as planetary exploration, unmanned delivery, and autonomous driving. However, ensuring high accuracy in practical applications is challenging due to enormous uncertainty inherent in real environment. In this paper, we aim to reveal the guideline for the design and implementation by investigating the path following performance of mobile robot controlled by the pure pursuit algorithm. To this end, we evaluate the accuracy of the pure pursuit algorithm when tuning the look ahead distance and deploying erroneous actuator.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.4
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• pp.27-40
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• 1996

This paper proposed a kinematic modeling methodlogy and feedback control system based on kinematics for 2 degrees of freedom of 4-wheeled mobile robot. We assigned coordinate systems to specify the transformation matirx and write the kinematic equation of motion. We derived the actuated inverse and sensed forwared solution for the calculation of actual robot orientation and the desired robot orientation. It is the most significant error and has the largest impact on the motion accuracy. To calculate the WMR position in real time, we introduced the dead-reckoning algorithm and composed two feedback control system that is based on kinematics. Through the simulation result, we compare with the ffedback control system for position control.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.4 no.1
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• pp.23-28
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• 2004

This paper proposes a sensor-fusion technique where the data sets for the previous moments are properly transformed and fused into the current data sets to enable accurate measurement, such as, distance to an obstacle and location of the service robot itself. In the conventional fusion schemes, the measurement is dependent on the current data sets. As the results, more of sensors are required to measure a certain physical parameter or to improve the accuracy of the measurement. However, in this approach, instead of adding more sensors to the system, the temporal sequence of the data sets are stored and utilized for the measurement improvement. Theoretical basis is illustrated by examples and the effectiveness is proved through the simulations. Finally, the new space and time sensor fusion(STSF) scheme is applied to the control of a mobile robot in an unstructured environment as well as structured environment.

• International Journal of Safety
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• v.1 no.1
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• pp.1-6
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• 2002

It is important to control the high accurate position and force to prevent unexpected accidents by a robot manipulator. Direct-drive robots are suitable to the position and force control with high accuracy, but it is difficult to design a controller because of the system's nonlinearity and link-interactions. This paper is concerned with the study of the stabilization force control of direct-drive robots. The proposed algorithm is consists of the feedback controllers and the neural networks. After the completion of learning, the outputs of feedback controllers are nearly equal to zero, and the neural networks play an important role in the control system. Therefore, the optimum adjustment of control parameters is unnecessary. In other words, the proposed algorithm does not need any knowledge of the controlled system in advance. The effectiveness of the proposed algorithm is demonstrated by the experiment on the force control of a parallelogram link-type robot.

• Proceedings of the KIEE Conference
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• 2009.07a
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• pp.1812_1813
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• 2009

This paper presents an accurate indoor localization method of a mobile robot using ultrasonic sensors. The coordinates of mobile robot are calculated by using trilateration which is using the distance between the transmitter and receiver. At this time, the distances can't be accurately calculated by containing noise. We propose Extended Kalman Filter(EKF) to improve estimation accuracy. The performance of proposed EKF is evaluated by simulation program. As a result, we confirm that the errors in estimate of mobile robot's position are eliminated from measured distance.

• International Journal of Precision Engineering and Manufacturing
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• v.4 no.1
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• pp.43-48
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• 2003

A linear laser-vision sensor called ‘Perception TriCam Contour' is mounted on an industrial robot and often used for various application of the robot such as the position correction and the inspection of a part. In this paper, a sensor center position calibration is presented for the most accurate use of the robot-Perceptron system. The obtained algorithm is suitable for on-site calibration in an industrial application environment. The calibration algorithm requires the joint sensor readings, and the Perceptron sensor measurements on a specially devised jig which is essential for this calibration process. The algorithm is implemented on the Hyundai 7602 AP robot, and Perceptron's measurement accuracy is increased up to less than 1.4mm.

• The Journal of Korea Robotics Society
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• v.15 no.2
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• pp.169-176
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• 2020

This paper studied the collision detection of robot manipulators for safe collaboration in human-robot interaction. Based on sensor-based collision detection, external torque is detached from subtracting robot dynamics. To detect collision using joint torque sensor data, a comparative study was conducted using data-based machine learning algorithm. Data was collected from the actual 3 degree-of-freedom (DOF) robot manipulator, and the data was labeled by threshold and handwork. Using support vector machine (SVM), decision tree and k-nearest neighbors KNN method, we derive the optimal parameters of each algorithm and compare the collision classification performance. The simulation results are analyzed for each method, and we confirmed that by an optimal collision status detection model with high prediction accuracy.