• Journal of the Korean Society of Industry Convergence
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• v.19 no.4
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• pp.167-175
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• 2016

We present a method for improving adaptability of Learning from Demonstration (LfD) strategy by combining the LfD and Particle Swarm Optimization (PSO). A trajectory generated from an LfD is modified with PSO by minimizing a fitness function that considers constraints. Finally, the final trajectory is suitable for a task and adapted for constraints. The effectiveness of the method is shown with a target reaching task with a manipulator in three-dimensional space.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.39 no.6
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• pp.638-648
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• 1990

An effective resolved motion control method of redundant manipulators is proposed to minimize the energy consumption and to increase the dexterity while satisfying the physical actuator constraints. The method employs the neural optimization networks, where the computation of Jacobian matrix is not required. Specifically, end effector movement resulting from each joint differential motion is first separated into orthogonal and tangential components with respect to a given desired trajectory. Then the resolved motion is obtained by neural optimization networks in such a way that 1) linear combination of the orthogonal components should be null 2) linear combination of the tangential components should be the differential length of the desired trajectory, 3) differential joint motion limit is not violated, and 4) weighted sum of the square of each differential joint motion is minimized. Here the weighting factors are controlled by a newly defined joint dexterity measure as the ratio of the tangential and orthogonal components.

• International Journal of Aeronautical and Space Sciences
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• v.8 no.1
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• pp.54-65
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• 2007

Parameter optimization technique is applied to planning UAVs(Unmanned Aerial Vehicles) path under artificial enemy radar threats. The ground enemy radar threats are characterized in terms of RCS(Radar Cross Section) parameter which is a measure of exposure to the radar threats. Mathematical model of the RCS parameter is constructed by a simple mathematical function in the three-dimensional space. The RCS model is directly linked to the UAVs attitude angles in generating a desired trajectory by reducing the RCS parameter. The RCS parameter is explicitly included in a performance index for optimization. The resultant UAVs trajectory satisfies geometrical boundary conditions while minimizing a weighted combination of the flight time and the measure of ground radar threat expressed in RCS.

• International Journal of Control, Automation, and Systems
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• v.6 no.3
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• pp.401-412
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• 2008

This paper discusses a design methodology of cooperative path planning for dynamical multi-agent systems with spatial and temporal constraints. The cooperative behavior of the multi-agent systems is specified in terms of the objective function in an optimization formulation. The path of achieving cooperative tasks is then generated by the optimization formulation constructed based on a differential flatness approach. Three scenarios of multi-agent tasking are proposed at the cooperative task planning framework. Given agent dynamics, both spatial and temporal constraints are considered in the path planning. The path planning algorithm first finds trajectory curves in a lower-dimensional space and then parameterizes the curves by a set of B-spline representations. The coefficients of the B-spline curves are further solved by a sequential quadratic programming solver to achieve the optimization objective and satisfy these constraints. Finally, several illustrative examples of cooperative path/task planning are presented.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.2
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• pp.382-390
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• 2009

This paper newly proposes a modular type dynamic encoding algorithm for searches (DEAS) which partitions the whole parameters into several modules and carries out exhaustive DEAS for each module. uDEAS is used to measure parameter sensitivities to the cost function, and the variables whose sensitivities are similar are grouped to make a module. The proposed optimization method is applied to optimal trajectory generation for biped walking of a humanoid. and the optimization result is compared with those of the former versions of DEAS.

• Proceedings of the KIEE Conference
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• 2003.07d
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• pp.2405-2407
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• 2003

This study deals with the gait optimization of via points on biped robot. ZMP(Zero Moment Point) is most important index in a biped robot's dynamic walking stability. To stable walking of a biped robot, legs's trajectory and a desired ZMP trajectory is required, balancing weight's movement is solved by FDM(Finite Difference Method). In this study, optimal index is defined to dynamically static walking of a biped robot, and optimization of via points is applied by GA(Genetic Algorithm).

• Advances in aircraft and spacecraft science
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• v.9 no.5
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• pp.401-414
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• 2022

In the present paper, the optimal selection of batteries for an electric pump-fed hybrid rocket engine is analyzed. A two-stage Mars Ascent Vehicle, suitable for the Mars Sample Return Mission, is considered as test case. A single engine is employed in the second stage, whereas the first stage uses a cluster of two engines. The initial mass of the launcher is equal to 500 kg and the same hybrid rocket engine is considered for both stages. Ragone plot-based correlations are embedded in the optimization process in order to chose the optimal values of specific energy and specific power, which minimize the battery mass ad hoc for the optimized engine design and ascent trajectory. Results show that a payload close to 100 kg is achievable considering the current commercial battery technology.

• Journal of the Korea Computer Graphics Society
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• v.21 no.5
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• pp.11-19
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• 2015

Our research introduces a novel system for creating 3D vehicle animation. Our system is for intuitively authoring vehicle accident scenes according to videos or based on user-drawn trajectories. Our system has been implemented by combining three existing ideas. The first part is for obtaining 3D trajectory of a vehicle from black-box videos. The second part is a tracking algorithm that controls a vehicle to follow a given trajectory with small errors. The last part optimizes the vehicle control parameters so that the error between the input trajectory and simulated vehicle trajectory is minimized. We also simulate the deformation of the car due to an impact to achieve believable results in real-time.

• Journal of Institute of Control, Robotics and Systems
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• v.5 no.1
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• pp.105-114
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• 1999

By using the conceptual impedance and the elasticity of a serial chain of spring-damper system, a real-time collision-free trajectory generation algorithm is proposed. The reference points on a trajectory connected by the spring-damper system have a mechanism for self-Position adjustment to avoid a collision by the impedance, and the local adjustment of each reference point is propagated through the elasticity to a real robot at the end of the spring-damper system. As a result, the overall trajectory consisting of the reference points becomes free of collision with environmental obstacles and efficient having the shortest distance as possible. In this process, the reference points connected by the spring-damper system take role of virtual robot as global guidance for a real robot, and a cooperative optimization is carried out by the system of virtual robots. A control algorithm is proposed to implement the impedance for a car-like mobile robot.

• ETRI Journal
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• v.40 no.5
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• pp.653-663
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• 2018

Patients with spinal cord injuries cannot move their limbs using their intact muscles. A suitable controller can be used to move their arms by employing the functional electrical stimulation method. In this article, a fuzzy exponential sliding-mode controller is designed to move a musculoskeletal human arm model to track an optimal trajectory in the sagittal plane. This optimal arm trajectory is obtained by developing a policy for the central nervous system. In order to specify the optimal trajectory between two points, two dynamic and static optimal criteria are applied simultaneously. The first dynamic objective function is defined to minimize the joint torques, and the second static optimization is offered to minimize the muscle forces at each moment. In addition, fuzzy logic is used to tune the sliding-surface parameter to enable an appropriate tracking performance. Simulation results are evaluated and compared with experimental data for upward and downward movements of the human arm.