• Journal of the Korean Society of Manufacturing Process Engineers
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• v.20 no.9
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• pp.70-75
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• 2021

We developed a platform that was capable of autonomous steering in a furrow environment. It was developed to autonomously control steering by recognizing the furrow using a laser distance, three-axis tilt, and temperature sensor. The performance evaluation indicated that the autonomous steering success rate was 99.17%, and it was possible to climb up to 5° on the slope. The usage time was approximately 40 h, and the maximum speed was 6.7 km/h.

• Journal of Advanced Marine Engineering and Technology
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• v.33 no.2
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• pp.288-294
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• 2009

The purpose of this study is manufacturing of monolithic housing for modularization of steering gear. Monolithic housing is difficult to weld with only rotation and linear motion. It is for this reason that housing of joining parts have a slope of 76.3 degrees. For this reason, welding trajectory was measured by the cooperative controled robot system, and then allowing for measured results, we developed the dedicated system. The developed system can be welded by using only 3 axises in contrast with robot system using 8 axises in housing welding. In addition, we applied CMT and laser welding device to dedicated system and as a result of experiment, sound bead and excellent roundness could be obtained.

• Transactions of the Korean Society of Automotive Engineers
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• v.3 no.2
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• pp.86-94
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• 1995

For a driving vehicle, a self-excited vibration of a pair of steerable wheels about their steering axis accompanied by tramp is called shimmy. Shimmy is caused by the coupling effects of the complicated actions of wheel and tire and the tramp motion of front wheel axle. Because front axle is no longer used on passenger cars shimmy occurring is not considerable. But in commercial vehicles using front wheel axle suspension system shimmy should be considered in design process. In this paper, the model closed to a practical vehicle was developed to analyze the shimmy of a commercial vehicle, and the effects of various design parameters to shimmy were observed by dynamic simulation with multibody dynamics program, DADS. The validity of developed model and analysis results were verified by practical vehicle experiments.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.43 no.7
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• pp.648-656
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• 2015

Active SAR satellite's main maneuver is roll axis maneuver to change SAR antenna direction. In addition, yaw steering is required to minimize the doppler centroid variation. Thus, it is resonable to assign the torque/momentum capacity mostly to roll axis and then yaw axis. In this case, the pitch axis shows low agility performance. However, due to orbit maintenance, large angle maneuver about pitch axis is sometimes required. In this paper, we study the pitch axis maneuver time reduction through sequential rotation about roll and yaw axis. Since these two axes have high agility performance than pitch axis, maneuver time reduction is possible when large angle rotation about pitch axis is required.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2000.11a
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• pp.281-286
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• 2000

This paper describes a lateral guidance system of an unmanned vehicle, using a neural network model of magneto-resistive sensor and magnetic fields. The model equation was compared with experimental sensing data. We found that the experimental result has a negligible difference from the modeling equation result. We verified that the modeling equation can be used in the unmanned vehicle simulations. As the neural network controller acquires magnetic field values(B$\_$x/, B$\_$y/, B$\_$z/) from the three-axis, the controller outputs a steering angle. The controller uses the back-propagation algorithms of neural network. The learning pattern acquisition was obtained using computer simulation, which is more exact than human driving. The simulation program was developed in order to verify the acquisition of the learning pattern, learning itself, and the adequacy of the design controller. A computer simulation of the vehicle (including vehicle dynamics and steering) was used to verify the steering performance of the vehicle controller using the neural network. Good results were obtained. Also, the real unmanned electrical vehicle using neural network controller verified good results.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.7
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• pp.677-683
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• 2015

This paper proposes a helicopter direction adjustment system using barycenter shift. Most conventional methods for direction adjustment of uniaxial helicopters rely on the angle of inclination of the main rotor. However, the inherent burden of the bearing of the main rotor and serious abrasion of the helicopter using the above methods may results in loss of balance. To decrease abrasion and enhance the barycenter stability, the proposed method was used to shift the barycenter of the helicopter instead of the main rotor for direction adjustment. We set a biaxial ARM on a uniaxial helicopter to adjust the direction of ARM pointing as well as to realize stable direction control when the helicopter loses its balance. The method may enhance the landing safety of helicopters in emergencies. Uniaxial helicopters can be controlled under any environment by adjusting the motor parameters of the ARM which is dependent on the center of mass using neural network. The experiment results show that the helicopter can return to the starting position quickly under the external disturbance.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1460-1463
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• 2005

In this paper, analysis of magnetic marker for autonomous vehicle guidance system using 3-axis magnetic sensor propose. Position sensing is an important an estimation system of vehicle position and orientation on magnetic lane, which is a parameter of the steering controller for automated lane following is described. To verify that the magnetic dipole model could be applied to a magnetic unit paved in roadway, the analysis of the data 3-axis magnetic field measured experimentally.

• Journal of Magnetics
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• v.21 no.4
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• pp.616-621
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• 2016

This paper presents a new multifunctional active guidewire system for medical applications that uses a magnetic microrobot. The study demonstrated that the proposed microrobot system could swim and be controlled under Low-Reynolds-number (Re) environments in blood vessel models. The prototype of the robotic guidewire, which is driven within a three-axis Helmholtz coil system, consists of a guide-wire, spiral blade, drilling tip, and permanent magnet. The spiral-type microrobot showed stable active locomotion between 3 kA/m and 9.1 kA/m under driving frequency up to 70 Hz in a silicone oil (of viscosity 1000 cst). The microrobot produced a maximum moving velocity of $8.08{\times}10^{-3}m/s$ at 70 Hz and 9.1 kA/m. In particular, the robotic guidewire produced 3D locomotion with drilling in the three-axis Helmholtz coil system. We verified active locomotion, towing of guidewire, steering, and drilling of the proposed robotic guidewire system through experimental analyses.

• Journal of IKEEE
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• v.23 no.3
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• pp.844-851
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• 2019

As wearable technology is becoming more common and a part of our lives, there have been many efforts to offer various smart services with wearable devices, such as motion recognition, safety of driving, and so on. In this paper, we present a method that exploits the 9-axis inertial sensors embedded in a smartwatch to identify whether the user is a vehicle driver or not and to estimate the steering wheel turning direction in the vehicle. The system consists of three components: (i) position recognition, (ii) driver recognition, and (iii) steering-wheel turning detection components. We have developed a prototype system for detecting user's motion with Arduino boards and IMU sensors. Our experiments show high accuracy in recognizing the driver and in estimating the wheel rotation angle. The average experimental error was $11.77^{\circ}$ which is small enough to perceiver the turning direction of steering-wheel.

• Journal of Sensor Science and Technology
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• v.21 no.3
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• pp.198-203
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• 2012

In this paper, the driving information system of the bicycle has been studied by using the 3-axis acceleration sensor. The sensor module composed of 3-axis acceleration sensor and MCU(Microcontroller Unit) was mounted onto the handle of bicycle and the experiments were conducted on the flatland, uphill and downhill of bicycle road. Three axis acceleration values were converted to the pitch and roll angles, then four major compensation methods have been applied to achieve meaningful data for driving information system. The experimental results of pitch angles showed 2.46, -1.26, 7.79 degrees in case of flatland, uphill, downhill, respectively. When the steering handle turned to the left direction, roll angles showed -29.35, -41.67, -36.98 degrees at each road condition. With the right-turn, roll angles presented 20.05, 33.75, 24.44 degrees in case of flatland, uphill, and downhill, respectively. The pitch angle has been increased more than 40 degrees at stop mode. By using the change of pitch and roll angles, we could obtain the driving information system of bicycle successfully.