• The Transactions of The Korean Institute of Electrical Engineers
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• v.63 no.3
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• pp.389-394
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• 2014

Two evolutionary gait generation methods for Cartesian and Joint coordinates space are compared to develop a fast locomotion for quadruped robots. GA(Genetic Algorithm) based approaches seek to optimize a pre-selected set of parameters for the locus of paw and initial position in cartesian coordinates space. GP(Genetic Programming) based technique generate few joint trajectories using symbolic regression in joint coordinates space as a form of polynomials. Optimization for two proposed methods are executed using Webots simulation for the quadruped robot which is built by Bioloid. Furthermore, simulation results for two proposed methods are analysed in terms of different coordinate spaces.

• Proceedings of the KIEE Conference
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• 1996.07b
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• pp.1212-1215
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• 1996

As usual systems, robot manipulators have also physical constraints for operating. It is a difficult problem that we operate manipulator in the minimal time under these constraints. In this pater, we solve this problem dividing it into two steps. In the first step, we find the minimal time trajectories by optimizing qubic polynomial joint trajectories using evolutionary algorithms. In the second step, we optimize controller for robot manipulator to track precisely trajectories optimized in the previous step.

• Journal of Korea Technology Innovation Society
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• v.7 no.3
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• pp.607-640
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• 2004

This article analyzes the venture firm based upon the new framework of Dynamic Firm Capability (DFC) to identify the process mechanism. Research methodology includes the case study involving structured interview and data collection from two leading Korean ICT(Information Communication Technology) firms in the same sector (DVR). IDIS, spun off from the university, has accumulated the innovative capability based on the R&D department. On the other hand, KODICOM has retained the technological trajectory in terms of marketing competence. Underlying hypothesis is that a firm should show a idiosyncratic evolutionary pattern by acquiring different complimentary assets(CA). In addition, effective internal process should be matched with the essential characteristics not only at the firm level but also at the sectoral level. By analyzing those two different firms, we will find the strategic successful factors based upon the evolutionary point of view. It is a key contribution of this paper to study on the process mechanism of ventures, and to explain detailed process mechanism by viewing two different characteristics of the firm at the functional level.

• Journal of Science and Technology Studies
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• v.3 no.2 s.6
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• pp.61-82
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• 2003

In a new paradigm of competition, firms face a multiple industry in a generation and compete with existing capabilities and resources in a new industry. Firms need to increase dynamic capabilities to adjust to a radical change in terms of technologies for survival and sustainable growth in a new industry. But we lack a clear conceptual model explaining evolutionary process of firms facing a emerging industry with different experiences in a prior industry and where heterogeneity in firms' technological portfolios come from. How we explaining firms' heterogeneity arising in a new industiy? In this article, I suggest hypothesis explaining firms' heterogeneity in a new industry with the concept of existent industry's technological trajectories, available assets, core processes and show the possibility of model to explain the heterogeneity of firms.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10a
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• pp.69-72
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• 1996

This paper considers a global resolution of kinematic redundancy under inequality constraints as a constrained optimal control. In this formulation, joint limits and obstacles are regarded as state variable inequality constraints, and joint velocity limits as control variable inequality constraints. Necessary and sufficient conditions are derived by using Pontryagin's minimum principle and penalty function method. These conditions leads to a two-point boundary-value problem (TPBVP) with natural, periodic and inequality boundary conditions. In order to solve the TPBVP and to find a global minimum, a numerical algorithm, named two-stage algorithm, is presented. Given initial joint pose, the first stage finds the optimal joint trajectory and its corresponding minimum performance cost. The second stage searches for the optimal initial joint pose with globally minimum cost in the self-motion manifold. The effectiveness of the proposed algorithm is demonstrated through a simulation with a 3-dof planar redundant manipulator.

• International Journal of Control, Automation, and Systems
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• v.4 no.4
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• pp.466-479
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• 2006

This paper addresses a formation navigation issue for a group of mobile robots passing through an environment with either static or moving obstacles meanwhile keeping a fixed formation shape. Based on Lyapunov function and graph theory, a NN formation control is proposed, which guarantees to maintain a formation if the formation pattern is $C^k,\;k\geq1$. In the process of navigation, the leader can generate a proper trajectory to lead formation and avoid moving obstacles according to the obtained information. An evolutionary computational technique using particle swarm optimization (PSO) is proposed for motion planning so that the formation is kept as $C^1$ function. The simulation results demonstrate that this algorithm is effective and the experimental studies validate the formation ability of the multiple mobile robots system.

• Journal of the Korea Institute of Military Science and Technology
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• v.12 no.3
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• pp.272-281
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• 2009

In this paper, three-dimensional optimal evasive maneuver patterns for air-to-surface attack missiles against proportionally navigated anti-air defense missiles were investigated. An interception error of the defense missile is produced by an evasive maneuver of the attack missile. It is assumed that the defense missiles are continuously launched during the flight of attack missile. The performance index to be minimized is then defined as the negative square integral of the interception errors. The direct parameter optimization technique based on SQP and a co-evolution method based on the augmented Lagrangian formulation are adopted to get the attack missile's optimal evasive maneuver patterns. The overall shape of the resultant optimal evasive maneuver is represented as a deformed barrel-roll.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.6
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• pp.573-579
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• 2008

This paper introduces a new approach to develop a fast gait for quadruped robot using GP(genetic programming). Planning gaits for legged robots is a challenging task that requires optimizing parameters in a highly irregular and multidimensional space. Several recent approaches have focused on using GA(genetic algorithm) to generate gait automatically and shown significant improvement over previous results. Most of current GA based approaches used pre-selected parameters, but it is difficult to select the appropriate parameters for the optimization of gait. To overcome these problems, we proposed an efficient approach which optimizes joint angle trajectories using genetic programming. Our GP based method has obtained much better results than GA based approaches for experiments of Sony AIBO ERS-7 in Webots environment.

• Proceedings of the KIEE Conference
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• 1994.11a
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• pp.359-361
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• 1994

This paper propose a Neural - GA-ES DC motor speed controller. The purpose is to achieve accurate trajectory control of the motor speed. A feedforward neural network structure is used for the controller. Genetic algorithm and evolution strategy is used for learning controller. Simulations are performed to demonstrate the effectiveness of proposed genetic algorithm and evolution strategy with neural structure.

• Smart Structures and Systems
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• v.26 no.6
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• pp.797-807
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• 2020

Due to the influence of nonlinearity and time-variation, it is difficult to establish an accurate model of concrete frame structures that adopt active controllers. Fuzzy theory is a relatively appropriate method but susceptible to human subjective experience to decrease the performance. This paper proposes a novel artificial intelligence based EBA (Evolved Bat Algorithm) controller with machine learning matched membership functions in the complex nonlinear system. The proposed affine transformed membership functions are adopted and stabilization and performance criterion of the closed-loop fuzzy systems are obtained through a new parametrized linear matrix inequality which is rearranged by machine learning affine matched membership functions. The trajectory of the closed-loop dithered system and that of the closed-loop fuzzy relaxed system can be made as close as desired. This enables us to get a rigorous prediction of stability of the closed-loop dithered system by establishing that of the closed-loop fuzzy relaxed system.