• Transactions of the Korean Society of Automotive Engineers
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• v.3 no.2
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• pp.16-29
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• 1995

In this study a tracked vehicle is idealized as a 2-dimensional 9-degrees-of-freedom model which takes into account the effects of HSU units, torsion bars, and track. For the model equations of motion are derived using Kane's method. By using the equations of motion, a numerical example is solved and results are compared to those obtained by using a general purpose multi body dynamic analysis program. The comparison study shows the reasonable coherence between the two results. which confirms the effectiveness of the model. With the model, dynamic response optimization is carried out. The objective function is the peak value of the vertical acceleration of the vehicle at the driver's seat, and the constraints are the wheel travel limits, the ground clearance. and the limits of other design variables. Three different sets of design variables are chosen and used for the optimization. The results show the attenuation of the acceleration peak value. Thus the procedure presented in this study can be utilized for the design improvement of the real system.

• The Journal of Korea Robotics Society
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• v.15 no.3
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• pp.212-220
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• 2020

This paper deals with a strategy of gain optimization for the kinematic control algorithm of a wire-driven surgical robot. The proposed controller consists of the closed-loop inverse kinematics with the back-calculation method. The closed-loop inverse kinematics has 18 PID control gains, and the back-calculation method has 6 gains. An efficient strategy is designed to optimize 18 values first and then the remaining 6 values. The optimal gain sets are searched under the step input with performance indices. In this gain optimization, the objective function is defined as the minimum value of signal-to-noise ratio of the performance indices for 6 DoF (Degree-of-Freedom) motion that is based on the Taguchi method, and the constraints are applied to obtain stable responses for each motion evenly. The gain sets obtained are verified by simulations using the test trajectories. In comparative results, the optimal gain value based on the performance index combined with ISE (integral of square error) and settling time showed the best control performance.

• Journal of the Korean Society for Precision Engineering
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• v.30 no.10
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• pp.1031-1039
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• 2013

This paper presents gain optimization of a 6-DOF underwater robotic platform with 4 rotatable thrusters. To stabilize the 6-DOF motion of the underwater robotic platform, a back-stepping controller is designed with 6 proportional gains and 6 derivative gains. The 12 gains of the backstepping controller are optimized to decrease settling time in step response in 6-DOF motion independently. Stability criterion and overshoots are used as a constraint of the optimization problem. Trust-region algorithm and hybrid Taguchi-Random order Coordinate search algorithm are used to determine the optimal parameters, and the results by two methods are analyzed. Additionally, the resulting controller shows improved performance under disturbances.

• Smart Structures and Systems
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• v.31 no.4
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• pp.409-419
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• 2023

Structural integrity can be accessed from dynamic deformations of structures. Moreover, dynamic deformations can be acquired from non-contact sensors such as video cameras. Kanade-Lucas-Tomasi (KLT) algorithm is one of the commonly used methods for motion tracking. However, averaging throughout the extracted features would induce bias in the measurement. In addition, pixel-wise measurements can be converted to physical units through camera intrinsic. Still, the depth information is unreachable without prior knowledge of the space information. The assigned homogeneous coordinates would then mismatch manually selected feature points, resulting in measurement errors during coordinate transformation. In this study, a two-stage optimization method for video-based measurements is proposed. The manually selected feature points are first optimized by minimizing the errors compared with the homogeneous coordinate. Then, the optimized points are utilized for the KLT algorithm to extract displacements through inverse projection. Two additional criteria are employed to eliminate outliers from KLT, resulting in more reliable displacement responses. The second-stage optimization subsequently fine-tunes the geometry of the selected coordinates. The optimization process also considers the number of interpolation points at different depths of an image to reduce the effect of out-of-plane motions. As a result, the proposed method is numerically investigated by using a truss bridge as a physics-based graphic model (PBGM) to extract high-accuracy displacements from recorded videos under various capturing angles and structural conditions.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.10
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• pp.1029-1037
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• 2008

When a humanoid robot pushes an object with its force, it is essential to adequately control its posture so as to maximize the surplus torque far all joints. For such purpose, this study proposes a method to find an optimal posture of a humanoid robot using a genetic algorithm in such a way that the surplus torque for all joints is maximized. In this study, pushing motion of an 18-DOF humanoid robot is considered. When the robot takes a cooperative motion to push an object, the palms and soles are assumed to be fixed at the object and ground respectively, and are subjected to sense the reaction force from the object and the ground. Then, the torques for all joints are calculated and reflected to fitness function of the genetic algorithm. To verify the effectiveness of the proposed method, a number of simulations with different fitness functions are carried out. The simulation result shows that the proposed method can be adopted to find optimized posture in cooperative motion of a humanoid robot.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.17 no.3
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• pp.40-46
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• 2008

This paper presents the optimal motion control for 3-axis SCARA robot by using $LabVIEW^{(R)}$. Specifically, for optimal motion control of 3-axis SCARA robot, we study velocity profile based on finite jerk(the first derivative of acceleration) and optimal gain tunig based on frequency response method by using $LabVIEW^{(R)}$. The velocity optimization with finite jerk aims at generating the smooth velocity profile of robot. Velocity profile based on finite jerk is acquired and applied to 3-axis SCARA robot by using $LabVIEW^{(R)}$. DSA(Dynamic Signal Analyzer) for frequency response method is programed by using $LabVIEW^{(R)}$. We obtain the bode plot of transfer function about 3-axis SCARA robot by using DSA, and perform the gain tuning considering dynamic characteristic based on the bode plot. These experiments have shown that the proposed motion control can reduce vibration displacement and response error rate each 33.7% and 51.7% of 3-axis SCARA robot.

• Structural Engineering and Mechanics
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• v.52 no.2
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• pp.405-426
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• 2014

In this paper, a new meta-heuristic algorithm named Ranked Particles Optimization (RPO), is presented. This algorithm is not inspired from natural or physical phenomena. However, it is based on numerous researches in the field of meta-heuristic optimization algorithms. In this algorithm, like other meta-heuristic algorithms, optimization process starts with by producing a population of random solutions, Particles, located in the feasible search space. In the next step, cost functions corresponding to all random particles are evaluated and some of those having minimum cost functions are stored. These particles are ranked and their weighted average is calculated and named Ranked Center. New solutions are produced by moving each particle along its previous motion, the ranked center, and the best particle found thus far. The robustness of this algorithm is verified by solving some mathematical and structural optimization problems. Simplicity of implementation and reaching to desired solution are two main characteristics of this algorithm.

• Proceedings of the IEEK Conference
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• 2003.11a
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• pp.433-436
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• 2003

In this paper, the efficient motion estimation and compensation method for 3 dimensional wavelet transform is proposed. Recently, since the compression performance and scalable functionality are provided by wavelet transform, many researches have been carried out for applying to the video compression. For the temporal filtering, motion estimation and compensation techniques are used, but the unconnected pixels, which are produced by motion compensation result into the degradation of coding performance and quality of the picture. For the efficient motion compensated temporal filtering by reducing the number of these unconnected pixels, we propose the variable block size motion estimation and compensation method. Also we propose a method that determines the block size using rate-distortion optimization technique according to the local characteristics of the frame. The simulation results show the improved performances than the MPEG-4 scalable coding methods and the 3 dimensional wavelet coding methods using fixed block size motion estimation and compensation.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2000.11a
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• pp.691-694
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• 2000

In this paper, a motion control algorithm is proposed by using neural network system, which makes a robot arm successfully avoid unexpected obstacle when the robot is moving from the start to the goal position. During the motion, if there is an obstacle the vision system recognizes it. And in every time the optimization-algorithm quickly chooses a motion among the possible motions of robot. The proposed algorithm has a good avoidance characteristic in simulation.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.11C
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• pp.1077-1084
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• 2006

This paper proposed a fast algorithm to reduce the amount of calculation for inter prediction which takes a great deal of the operational time in H.264/AVC. This algorithm decides a search range according to the direction of predicted motion vector, and then performs an adaptive spiral search for the candidates with JM(Joint Model) FME(Fast Motion Estimation) which employs the rate-distortion optimization(RDO) method. Simultaneously, it decides a threshold cost value for each of the variable block sizes and performs the motion estimation for the variable search ranges with the threshold. These activities reduce the great amount of the complexity in inter prediction encoding. Experimental results by applying the proposed method .to various video sequences showed that the process time was decreased up to 80% comparing to the previous prediction methods. The degradation of video quality was only from 0.05dB to 0.19dB and the compression ratio decreased as small as 0.58% in average. Therefore, we are sure that the proposed method is an efficient method for the fast inter prediction.