• 제어로봇시스템학회:학술대회논문집
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• 1996.10a
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• pp.20-23
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• 1996

This paper deals with the flexible manipulator with rotational and translational degrees of freedom, which has an arm of time-varying length with the prismatic joint. The tracking control problem of the flexible manipulator is considered. First we design the controller of the 2-type robust servo system based on the finite horizon optimal control theory for the trajectory planned as a discontinuous velocity. Next, to reduce the tracking error, we use the method of the dynamic programming and of modifying the reference trajectory in time coordinate. The simulation results show that the dynamic modeling is adequate and that the asymptotic stabilization of the flexible manipulator is preserved in spite of nonlinear terms. The PTP control error has been reduced to zero completely, and the trajectory tracking errors are reduced sufficiently by the proposed control method.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.50 no.3
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• pp.143-148
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• 2001

A lot of robot trajectory tracking methods are proposed to enhance the tracking error, but irregular tracking errors are always accompanied and very hard to reduce it. Up to now, these irregular tracking errors are reduced by introducing more complicated control algorithms. But, it is intuitively obvious to reduce only the big errors selectively in the irregular ones for the better performance instead of using more complicated control algorithms. By the characteristics of the robot, big tracking errors of the end-effector are generated mostly due to the fast moving of joint. So, in this paper, we introduce a new method which reduce the big tracking errors by clippings the joint velocity with the constraint of given path. Using this method, desired trajectory tracking is obtained within the far reduced error bound. Also, this method is successfully applied to generate the path-constrained error reducing trajectories for 2-axis SCARA type robot.

• Transactions of the Korean Society of Automotive Engineers
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• v.4 no.2
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• pp.115-126
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• 1996

In order to obtain the principal design data for developing the Autonomous Robot Vehicle(ARV), Sensitivity analysis on the trajectory error and friction force with respect to the dynamic parameters is performed. In the straight motion, the trajectory error has been proved to be much affected by the mass variance of the ARV while the lateral friction force is much affected by the location of the mass center. In the curved motion, the effect of mass and moment of inertia is considered importantly. In addition, the lateral offset gives more effect than the geometric dimension of the ARV on the trajectory errors and friction force.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.2
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• pp.600-619
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• 2015

We propose a cost-efficient hybrid algorithm for online location updates that efficiently combines feature point detection with the online trajectory-based sampling algorithm. Our algorithm is designed to minimize the average trajectory error with the minimal number of sample points. The algorithm is composed of 3 steps. First, we choose corner points from the map as sample points because they will most likely cause fewer trajectory errors. By employing the online trajectory sampling algorithm as the second step, our algorithm detects several missing and important sample points to prevent unwanted trajectory errors. The final step improves cost efficiency by eliminating redundant sample points on straight paths. We evaluate the proposed algorithm with real GPS trajectory data for various bus routes and compare our algorithm with the existing one. Simulation results show that our algorithm decreases the average trajectory error 28% compared to the existing one. In terms of cost efficiency, simulation results show that our algorithm is 29% more cost efficient than the existing one with real GPS trajectory data.

• Journal of Institute of Control, Robotics and Systems
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• v.12 no.2
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• pp.145-153
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• 2006

An optimal capturing trajectory for a moving object is proposed in this paper based on the observation that a single-curvature path is more accurate than double-or triple-curvature paths. Moving distance, moving time, and trajectory error are major factors considered in deciding an optimal path for capturing the moving object. That is, the moving time and distance are minimized while the trajectory error is maintained as small as possible. The three major factors are compared for the single and the double curvature trajectories to show superiority of the single curvature trajectory. Based upon the single curvature trajectory, a kinematics model of a mobile robot is proposed to follow and capture the moving object, in this paper. A capturing scenario can be summarized as follows: 1. Motion of the moving object has been captured by a CCD camera., 2. Position of the moving object has been estimated using the image frames, and 3. The mobile robot tries to follow the moving object along the single curvature trajectory which matches positions and orientations of the moving object and the mobile robot at the final moment. Effectiveness of the single curvature trajectory modeling and capturing algorithm has been proved, through simulations and real experiments using a 2-DOF wheel-based mobile robot.

• Journal of Institute of Control, Robotics and Systems
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• v.4 no.5
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• pp.636-643
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• 1998

This paper is presents multivariable control scheme for industrial robot manipulators. The control scheme consists of two loops. The modeling error between linearized robot model and actual robot model is compensated in error compensation loop. The PID control loop is designed for pole assignment to stability of robot system and utilized for trajectory tracking. Alternatively computer simulation results are given for illustration purpose of suggested controller.

• Journal of the Korea Institute of Military Science and Technology
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• v.2 no.2
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• pp.218-225
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• 1999

This paper contains the computational simulation of a free rocket with a parachute and the development of a firing table for each range. To obtain the trajectory of the rocket, 6 DOF model of rocket with parachute was generated and the wind tunnel test was done for the input parameters. Good agreement was obtained between the analysis of trajectory and the flight test result. Also the trajectory error analysis was performed by the Monte Carlo simulation. As a result of simulation, the CEP(Circular Error Probability) of the firing table was calculated.

• Journal of Institute of Control, Robotics and Systems
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• v.12 no.6
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• pp.561-567
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• 2006

This paper deals with a fuzzy controller using IA(Immune Algorithm) for Trajectory Tracking of 2-DOF WMR(Wheeled Mobile Robot). The global inputs to the WMR are reference position and reference velocity, which are time variables. The global output of WMR is a current position. The tracking controller makes position error to be converged 0. In order to reduce position error, a compensation velocities on the track of trajectory is necessary. Therefore, a FIAC(Fuzzy-IA controller) is proposed to give velocity compensation in this system. Input variables of fuzzy part are position errors in every sampling time. The output values of fuzzy part are compensation velocities. IA are implemented to adjust the scaling factor of fuzzy part. The computer simulation is performed to get the result of trajectory tracking and to prove efficiency of proposed controller.

• 제어로봇시스템학회:학술대회논문집
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• 1989.10a
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• pp.627-634
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• 1989

A collision-free trajectory planning algorithm using the iterative learning concept is proposed for dual robot arms in a 3-D workspace to accurately follow their specified paths with constant velocities. Specifically, a collision-free trajectory minimizing the trajectory error is obtained first by employing the linear programming technique. Then the total operating time is iteratively adjusted based on the maximum trajectory error of the previous iteration so that the collision-free trajectory has no deviation from the specified path and also the operating time is near-minimal.

• Transactions of the Korean Society of Mechanical Engineers
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• v.15 no.1
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• pp.69-77
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• 1991

A collision-free trajectory planning algorithm using an iterative learning concept is proposed for dual robot arms in a 3-D common workspace to accurately follow their specified paths with constant velocities. Specifically, a collision-free trajectory minimizing the trajectory error is obtained first by employing the linear programming technique. Then the total operating time is iteratively adjusted based on the maximum trajectory error of the previous iteration so that the collision-free trajectory has no deviation from the specified path and also that the operating time is near-minimal. To show the validity of the proposed algorithm, a numerical example is presented based on two planar robots.