• Journal of Ocean Engineering and Technology
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• v.11 no.1
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• pp.84-95
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• 1997

This paper presents a new approach to the design speed and azimuth control of a mobile robot with drive wheel. The proposed control scheme uses a Gaussian function as a unit function in the fuzzy-neural network, and back propagation algorithm to train the fuzzy-neural network controller in the frmework of the specialized learning architecture. It is proposed a learning controller consisting of two neural network-fuzzy based on independent reasoning and a connection net with fixed weights to simple the neural networks-fuzzy. The performance of the proposed controller is shown by performing the computer simulation for trajectory tracking of the speed and azimuth of a mobile robot driven by two independent wheels.

• Journal of the Korean Society for Precision Engineering
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• v.15 no.3
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• pp.127-132
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• 1998

Mobile wheeled robots are nonholonomically constrained systems. Generally, it is very difficult to describe the motion of mechanical systems with nonintegrable nonholonomic constraints. An objective of this study is to describe the motion of a robot with a free wheel. The motion of holonomically and/or nonholonomically constrained system can be simply determined by Generalized Inverse Method presented by Udwadia and Kalaba in 1992. Using the method, we describe the exact motion of the robot and determine the constraint force exerted on the robot for satisfying constraints imposed on it. The application illustrates the ease with which the Generalized Inverse Method can be utilized for the purpose of control of nonlinear system without depending on any linearization, maintaining precision tracking motion and explicit determination of control forces of nonholonomically constrained system.

• Proceedings of the KSME Conference
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• 2001.06b
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• pp.416-421
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• 2001

It was firstly issued that frequently broken of Encoder installed at travelling motor during RTGC operation. Estimated as broken due to excessive vibration of traveling and motor manufacturer claimed it as resonance of motor base. The principal vibration of Encoder was caused by the rotating vibration component of motor and by traveling wheel. The component transmitted from the wheel didn't have great vibration by the resonance with motor and other parts. Therefore, the plans was tried to add the support point to prevent the Encoder shaft vibrated greatly and inhibit the vibration. These showed good results.

• Journal of the Korean Society of Mechanical Technology
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• v.13 no.2
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• pp.71-78
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• 2011

A kart is a vehicle without the suspension system and the differential gear. The kart frame as an elastic body plays the role of a spring. By the cornering of a kart, rolling, pitching and twisting motions are induced in the kart frame. Also the slip or noncontact of the wheel and a permanent deformation of the kart frame can be induced. In order to examine closely this phenomenon, measurement on height-displacements with various sensors and tracking system and analysis on the kart frame twisting characteristics with the rolling and pitching angle are needed. According to the measurement result, while driving in a curve at high speed the kart frame is quite twisted. Analysis on the measurement results shows that a kart used primarily in high speed requires a frame with low torsional stiffness and a frame material with high tensile strength and large elongation.

• International Journal of Highway Engineering
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• v.8 no.1 s.27
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• pp.77-87
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• 2006

Dynamic stability (DS) in the wheel tracking (WT) test is used as a basic index of rut-resistance for asphalt mixtures. In general, the deeper rut depth is obtained from the weaker mixture, resulting in the lower DS value. On the other hand, the shallower rut depth is obtained from the stronger mixture, resulting in the higher DS. However, it is not always the case when the DS is calculated by the existing method because the DS is simply determined based on the slope at the final stage of the rut depth-cycle curve. Specifically, in the case of the depth-cycle curve showing a steeper slope in the early part but flatter slope in last part, the DS is calculated to be higher than the curve showing a ever-increasing slope throughout the test. As long as the last part of slope is flatter, the deeper final rut depth is evaluated to show a higher DS than the little final rut depth. Therefore, a reasonable method for DS evaluation need to be established. Several new methods were suggested by considering the early, middle and final parts of rut depth to determine a reasonable DS. The results have shown that those new methods have demonstrated a significant improvement in distinguishing similarly performing mixtures. The result also showed that $DS_2$ had better correlation with SD than any other methods , representing the rutting resistance of asphalt mixture very well. The new DS calculation method is relatively simple and easy to follow. More validatin study is required for practical application.

• Proceedings of the KSR Conference
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• 2011.05a
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• pp.301-306
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• 2011

The rear of the vehicle generally overhangs the rear axle. As a result, the rear of a vehicle swings to the outside of the rear axle(rear swing-out). In front steering vehicles, rear swing-out is not important because rear swing-out values measured outside the rear edge are relatively small. However, in the case of the bimodal tram with AWS(all wheel steering), the rear swing-out values increase because of the rear steering at a reverse phase angle. Off-tracking is defined as the radial offset between the path of the centerline of the front axle and the path of the centerline of the following axle. In this paper, in addition to determine the turning performance of bimodal tram with AWS, turning radius, swing-out, off-tracking and swept path width were also investigated.

• IEMEK Journal of Embedded Systems and Applications
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• v.13 no.1
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• pp.33-43
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• 2018

In this paper, we describe an sound tracking mobile robot suitable for areas where GPS is not available. Sound sensors are attached to four sides of the robot in order to locate the person in a danger, and the robot is supposed to move to the yelling person. The traveling distance of the mobile robot is calculated by the encoder attached to the wheel of the mobile robot. The moving direction of the mobile robot is measured by a gyro sensor on the robot. When the person in danger pushes a button of the mobile robot, the mobile robot transmits the trajectory data to a designated server.

• Journal of Mechanical Science and Technology
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• v.16 no.2
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• pp.137-146
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• 2002

In this paper, a path generation algorithm that uses sensor scannings is described. A scanning algorithm for recognizing the ambient environment of the Automatic Guided Vehicle (AGV) that uses the information from the sensor platform is proposed. An algorithm for computing the real path and obstacle length is developed by using a scanning method that controls rotating of the sensors on the platform. The AGV can recognize the given path by adopting this algorithm. As the AGV with two-wheel drive constitute a nonholonomic system, a linearized kinematic model is applied to the AGV motor control. An optimal controller is designed for tracking the reference path which is generated by recognizing the path pattern. Based on experimental results, the proposed algorithm that uses scanning with a sensor platform employing only a small number of sensors and a low cost controller for the AGV is shown to be adequate for path generation.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2003.04a
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• pp.312-318
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• 2003

We propose a new technique for the cruise control system design of a mobile robot with three drive wheel. The proposed control scheme uses a Gaussian function as a unit function in the fuzzy neural network and back propagation algorithm to train the fuzzy neural network controller in the framework of the specialized teaming architecture. It is proposed a learning controller consisting of too neural network-fuzzy based on independent reasoning and a connection net with fixed weights to simply the neural networks-fuzzy. The performance of the proposed controller is shown by performing the computer simulation for trajectory tracking of the speed and azimuth of a mobile robot driven by three independent wheels.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2004.10a
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• pp.207-212
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• 2004

This paper presents a new approach to the design of cruise control system of a mobile robot with two drive wheel. The proposed control scheme uses a Gaussian function as a unit function in the fuzzy neural network, and back propagation algorithm to train the fuzzy neural network controller in the framework of the specialized learning architecture. It is proposed a learning controller consisting of two neural network-fuzzy based on independent reasoning and a connection net with fixed weights to simply the neural networks-fuzzy. The performance of the proposed controller is shown by performing the computer simulation for trajectory tracking of the speed and azimuth of a mobile robot driven by two independent wheels.