• Journal of the Korean Society of Industry Convergence
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• v.20 no.1
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• pp.49-55
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• 2017

This study proposes a new approach to Control and trajectory generation of a 8 DOF human robot arm with computational complexity and singularity problem. To deal with such problems, analytical methods for a redundant robot arm have been researched to enhance the performance of research, we propose an analytical kinematics algorithm for a 8 DOF bipped dual robot arm. Using this algorithm, it is possible to generate a trajectory passing through the singular points and intuitively move the elbow without regarding to the end-effector pose. Performance of the proposed algorithm was verified by simulation test with various conditions. It has been verified that the trajectory planning using this algorithm.

• Journal of Korea Multimedia Society
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• v.21 no.8
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• pp.969-981
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• 2018

Recent advances in machine learning approaches such as deep neural network and reinforcement learning offer significant performance improvements in generating detailed and varied motions in physically simulated virtual environments. The optimization methods are highly attractive because it allows for less understanding of underlying physics or mechanisms even for high-dimensional subtle control problems. In this paper, we propose an efficient learning method for stochastic policy represented as deep neural networks so that agent can generate various energetic motions adaptively to the changes of tasks and states without losing interactivity and robustness. This strategy could be realized by our novel trajectory search method motivated by the trust region policy optimization method. Our value-based trajectory smoothing technique finds stably learnable trajectories without consulting neural network responses directly. This policy is set as a trust region of the artificial neural network, so that it can learn the desired motion quickly.

• Proceedings of the KIEE Conference
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• 2005.07a
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• pp.310-312
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• 2005

An out-of-step condition results from the loss of the synchronism of the generators. A disturbance in a power system causes the generator angle to oscillate. When there is a severe disturbance such as a heavy current fault loss of major generation or loss of a large block of load the oscillation can be severe and even increase largely and finally the out-of-step condition may occur During the power swing and out-of-step conditions, the a apparent impedance at a relay location changes, and the power flow also changes as the angle difference is varied. This paper presents a method to analyze the trajectory of complex power during a power swing and out-of-step condition. The trajectory of the complex power is analyzed when a power swings and a fault occurs. Moreover, the complex power is analyzed when the ratios between the voltages at both sides and the line impedances are changed. These methods are verified through simulation using the ATP/EMTP MODELS.

• Journal of Institute of Control, Robotics and Systems
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• v.10 no.9
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• pp.833-839
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• 2004

This paper proposes a method that minimizes the consumed energy by searching the optimal locations of the mass centers of links composing of a biped robot using Real-Coded Genetic Algorithm. Generally, in order to utilize optimization algorithms, the system model and design variables must be defined. Firstly, the proposed model is a 6-DOF biped robot composed of seven links, since many of the essential characteristics of the human walking motion can be captured with a seven-link planar biped walking in the saggital plane. Next, Fourth order polynomials are used for basis functions to approximate the walking gait. The coefficients of the fourth order polynomials are defined as design variables. In order to use the method generating the optimal gait trajectory by searching the locations of mass centers of links, three variables are added to the total number of design variables. Real-Coded GA is used for optimization algorithm by reason of many advantages. Simulations and the comparison of three methods to generate gait trajectories including the GCIPM were performed. They show that the proposed method can decrease the consumed energy remarkably and be applied during the design phase of a robot actually.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.1
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• pp.77-83
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• 2005

This paper deals with determination of motions of a humanoid robot using genetic algorithm. A humanoid robot has some problems of the structural instability basically. So, we have to consider the stable walking gait in gait planning. Besides, it is important to make the smoothly optimal gait for saving the electric power. A mobile robot has a battery to move autonomously. But a humanoid robot needs more electric power in order to drive many joints. So, if movements of walking joints don't maintain optimally, it is difficult for a robot to have working time for a long time. Also, if a gait trajectory doesn't have optimal state, the expected life span of joints tends to be decreased. To solve these problems, the genetic algorithm is employed to guarantee the optimal gait trajectory. The fitness functions in a genetic algorithm are introduced to find out optimal trajectory, which enables the robot to have the less reduced jerk of joints and get smooth movement. With these all process accomplished by a PC-based program, the optimal solution could be obtained from the simulation. In addition, we discuss the design consideration for the joint motion and distributed computation of the humanoid, ISHURO, and suggest its result such as the structure of the network and a disturbance observer.

• Journal of Auto-vehicle Safety Association
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• v.11 no.3
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• pp.30-36
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• 2019

This paper suggests a car-following algorithm for urban environment, with multiple target candidates. Until now, advanced driver assistant systems (ADASs) and self-driving technologies have been researched to cope with diverse possible scenarios. Among them, car-following driving has been formed the groundwork of autonomous vehicle for its integrity and flexibility to other modes such as smart cruise system (SCC) and platooning. Although the field has a rich history, most researches has been focused on the shape of target trajectory, such as the order of interpolated polynomial, in simple single-lane situation. However, to introduce the car-following mode in urban environment, realistic situation should be reflected: multi-lane road, target's unstable driving tendency, obstacles. Therefore, the suggested car-following system includes both in-lane preceding vehicle and other factors such as side-lane targets. The algorithm is comprised of three parts: path candidate generation and optimal trajectory selection. In the first part, initial guesses of desired paths are calculated as polynomial function connecting host vehicle's state and vicinal vehicle's predicted future states. In the second part, final target trajectory is selected using quadratic cost function reflecting safeness, control input efficiency, and initial objective such as velocity. Finally, adjusted path and control input are calculated using model predictive control (MPC). The suggested algorithm's performance is verified using off-line simulation using Matlab; the results shows reasonable car-following motion planning.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.49 no.4
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• pp.263-272
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• 2021

In this study, aerodynamic coefficients obtained from Computational Fluid Dynamics (CFD) using wind tunnel test-like method is compared with coefficients obtained by actual wind tunnel test. Unsteady analysis has performed with using harmonic equation for motion of the external store. Aerodynamic database is generated based on CFD results to simulate 6 degree-of-freedom store separation analysis. Trajectory is obtained from simulation using both CFD-based and test-based database, and results are compared with trajectory from flight test result. It is concluded that generation of database based on CFD with wind tunnel test technique is valid from good agreement of the trajectory.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.228-231
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• 2003

This paper presents the leg trajectory generation for the quadruped robot with genetic-fuzzy algorithm. To have the nobility even at uneven terrain, a robot is able to recognize obstacles, and generates moving path of body that can avoid obstacles. This robot should have its own avoidance algorithm against obstacles, forwarding to target without collision. During walking period, n robot recognizes obstacle from external environment with a PSD and some interface, and this obstacle information is converted into proper the body rotation angle by fuzzy inference engine. After this process, we can infer the walking direction and walking distance of body, and finally can generate the optimal Beg trajectory using genetic algorithm. All these methods are verified with PC simulation program, and implemented to SERO-V robot.

• Proceedings of the KIEE Conference
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• 2011.07a
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• pp.1770-1771
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• 2011

In mission planning of UAV applications, especially for the missions requiring height transitions, it is required to generate reference flight trajectories considering the performances of the engine installed in the UAV. Even though the vertical line following guidance based height transition trajectory generation method has been developed to build reference height transition trajectories easily, it is not adequate for considering engine performances effectively since many engine characteristics and performances have conventionally been described in the V-H(speed-height) plane which is not the very space where the UAVs are actually flying. In this paper, we derive the trajectories in V-H plane for the vertical line following flights. And based on the results, a new algorithm to design the reference height transition trajectories for UAV applicaions. Simulation results demonstrate that the proposed algorithm is very effective and easily applicable.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.33 no.9
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• pp.922-929
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• 2009

This paper deals with the State-Dependent Riccati Equation (SDRE) Technique for the design of helicopter nonlinear waypoint guidance controller. To generate the flight guidance through multiple waypoints, we use the trigonometric spline. The controller design and its validation is based upon a level 2 simulation helicopter model and the designed SDRE controller is applied to the trajectory tracking problems. To validate the designed SDRE controller, the simulation environment of high fidelity helicopter model is developed using three independent computers. This paper focuses on the validation the present SDRE controller through the helicopter waypoint guidance simulation.