• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.3A
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• pp.256-268
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• 2008

This paper proposes an efficient scheme to track the time variant channel induced by multi-path Rayleigh fading in mobile wireless Multiple Input Multiple Output-Orthogonal Frequency Division Multiplexing (MIMO-OFDM) systems with null sub-carriers. In the proposed method, a blind channel response predictor is designed to cope with the time variant channel. The proposed channel tracking scheme consists of a frequency domain estimation approach that is coupled with a Minimum Mean Square Error (MMSE) time domain estimation method, and does not require any matrix inverse calculation during each OFDM symbol. The main attributes of the proposed scheme are its reduced computational complexity and good tracking performance of channel variations. The simulation results show that the proposed method exhibits superior performance than the conventional channel tracking method [4] in time varying channel environments. At a Doppler frequency of 100Hz and bit error rates (BER) of 10-4, signal-to-noise power ratio (Eb/N0) gains of about 2.5dB are achieved relative to the conventional channel tracking method [4]. At a Doppler frequency of 200Hz, the performance difference between the proposed method and conventional one becomes much larger.

• Journal of the Korea Computer Industry Society
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• v.5 no.9
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• pp.993-1004
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• 2004

We propose the method for kinematic and dynamic modeling and Path-tracking of four-wheeled mobile robots with 2 d.o.f having the limited drive-torques. Controllability of wheeled-mobile robots is revealed by using the kinematic model. Instantaneously coincident coordinate system, force/torque propagation and Newton's equilibrium law are used to induce the dynamic model. When drive-torques generated by inverse dynamics exceed the limitation, we make wheeled-mobile robots follow the reference path by modifying the planned reference trajectory with time-scaling. The controller is introduced to compensate for error owing to modeling uncertainty and measurement noise. And simulation results prove that the method proposed by this paper is efficient.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.7
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• pp.599-604
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• 2013

Path planning of mobile robots has a purpose to design an optimal path from an initial position to a target point. Minimum driving time, minimum driving distance and minimum driving error might be considered in choosing the optimal path and are correlated to each other. In this paper, an efficient driving trajectory is planned in a real situation where a mobile robot follows a moving object. Position and distance of the moving object are obtained using a web camera, and the rotation angular and linear velocities are estimated using Kalman filters to predict the trajectory of the moving object. Finally, the mobile robot follows the moving object using a single curvature trajectory by estimating the trajectory of the moving object. Using the estimation by Kalman filters and the single curvature in the trajectory planning, the total tracking distance and time saved amounts to about 7%. The effectiveness of the proposed algorithm has been verified through real tracking experiments.

• Journal of Drive and Control
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• v.17 no.4
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• pp.80-86
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• 2020

Autonomous driving is one of the most important new technologies of our time; it has benefits in terms of safety, the environment, and economic issues. Path following algorithms, such as automated lane keeping systems (ALKSs), are key level 3 or higher functions of autonomous driving. Pure-Pursuit and Stanley controllers are widely used because of their good path tracking performance and simplicity. However, with the Pure-Pursuit controller, corner cutting behavior occurs on curved roads, and the Stanley controller has a risk of divergence depending on the response of the steering system. In this study, we use the advantages of each controller to propose a hybrid control strategy that can be stably applied to complex driving environments. The weight of each controller is determined from the global and local curvature indexes calculated from HD map information and the current driving speed. Our experimental results demonstrate the ability of the hybrid controller, which had a cross-track error of under 0.1 m in a virtual environment that simulates K-City, with complex driving environments such as urban areas, community roads, and high-speed driving roads.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.35 no.11
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• pp.1491-1497
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• 2011

One of the primary concerns in the design of welding devices is how to reduce the distance error between the welding path and the torch, especially when the path has a combination of circular and linear parts. This study investigated a mechanism for reducing the tracking error in the tangent area of a circular and linear path. A portable welding device, called a carriage, has been designed for a specific welding path by considering the distance error deviation. This welding carriage for vertical cover plate welding consists of a rail, a welding torch and the carriage body itself.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.18 no.6
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• pp.229-235
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• 2018

Research on indoor location tracking technology using smart phone is actively being carried out. Especially, in order to display the movement path of the smartphone on the map, the azimuth angle should be estimated by using the geomagnetic sensor built in most smart phones. Due to the distortion of the magnetic field due to the surrounding steel structure and the inclination of the smartphone, the estimation error of azimuthal angle may be occurred. In this paper, we propose a correction method of the geomagnetic sensor at the stationary state and a correction method for the inclination of the smartphone. We also propose a method to correct the azimuth error due to the difference between the magnetic north and the grid north.

• Journal of Navigation and Port Research
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• v.42 no.2
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• pp.87-96
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• 2018

A trajectory control system plays an important role in controlling motions of marine vehicle when a series of way points or a path is given. In this paper, a sliding mode control (SMC)-based trajectory tracking controller for marine vehicles is presented. A small-sized unmanned ship is considered as a control object. Both speed and heading angle of a ship should be controlled for tracking control. The common point of related researches was to separate ship's speed and heading angle in control methods. In this research, a new control law from a general sliding mode theory that can be applied to MIMO (multi input multi output) system is derived and both speed and heading angle of a ship can be controlled simultaneously. The propulsion force and rudder force are also applied in modeling stage to achieve accurate simulation. Disturbance induced by wind is also tackled in the dynamics considering robustness of the proposed control scheme. In the simulation, we employed a way-point method to generate ship's trajectory and applied the proposed control scheme to ship's trajectory tracking control. Our results confirmed that the tracking error was converged to zero, thus demonstrating the effectiveness of the proposed method.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.2
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• pp.265-276
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• 2017

In this paper, a robust and more accurate trajectory tracking control method for a mobile robot is proposed using WIPDC(Weighted Integral Parallel Distributed Compensation) and T-S Fuzzy disturbance observer. WIPDC reduces the steady state error by adding weighted integral term to PDC. And, T-S Fuzzy disturbance observer makes it possible to estimate and cancel disturbances for a T-S fuzzy model system. As a result, the trajectory tracking controller based on T-S Fuzzy disturbance observer shows robust tracking performance. When the initial postures of a mobile robot and the reference trajectory are different, the initial control inputs to the mobile robot become too large to apply them practically. In this study, also, the problem is solved by designing an initial approach path using a path planning method which employs $B\acute{e}zier$ curve with acceleration limits. Performances of the proposed method are proved from the simulation results.

• Journal of the Korean Society for Precision Engineering
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• v.23 no.1 s.178
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• pp.113-120
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• 2006

This paper proposed the control algorithm fur aspheric surface grinding and was verified by the experiment. The functions of the algorithm were simultaneous control of the position and interpolation of the aspheric curve. The non-linear formula of the tool position was derived from the aspheric equations and the shape of the tool. The function was partitioned by an certain interval and the control parameters were calculated at each control section. The movement in a session was interpolated with acceleration and velocity. The position error was feed-backed by rotary encorder. The concept of feedback algorithm was correcting position error by increasing or decreasing the speed. In the experiment, two-axis machine was controlled to track the aspheric surface by the proposed algorithm. The effect of the control and process parameters was monitored. The result showed that the maximum tracking error was under sub-micro level for the concave and convex surfaces.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.2
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• pp.168-177
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• 2008

Path finding is a key element in the navigation of a mobile robot. To find a path, robot should know their position exactly, since the position error exposes a robot to many dangerous conditions. It could make a robot move to a wrong direction so that it may have damage by collision by the surrounding obstacles. We propose a method obtaining an accurate robot position. The localization of a mobile robot in its working environment performs by using a vision system and Virtual Reality Modeling Language(VRML). The robot identifies landmarks located in the environment. An image processing and neural network pattern matching techniques have been applied to find location of the robot. After the self-positioning procedure, the 2-D scene of the vision is overlaid onto a VRML scene. This paper describes how to realize the self-positioning, and shows the overlay between the 2-D and VRML scenes. The suggested method defines a robot's path successfully. An experiment using the suggested algorithm apply to a mobile robot has been performed and the result shows a good path tracking.