• Journal of Power System Engineering
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• v.21 no.5
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• pp.41-47
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• 2017

To implement Argentina tango dancer-like walking of the humanoid robot, a new trajectory generation scheme based on particle swarm optimization of the blending polynomial is presented. Firstly, the characteristics of Argentina tango walking are derived from observation of tango dance. Secondly, these are reflected in walking pose conditions and cost functions of particle swarm optimization to determine the coefficients of blending polynomial. For the stability of biped walking, zero moment point and reference trajectory of swing foot are also included in cost function. Thirdly, after tango walking cycle is divided into 3 stages with 2 postures, optimal trajectories of ankles, knees and hip of lower body, which include 6 sagittal and 4 coronal angles, are derived in consequence of optimization. Finally, the feasibility of the proposed scheme is validated by simulating biped walking of humanoid robot with derived trajectories under the 3D Simscape environment.

• Korean Journal of Computational Design and Engineering
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• v.2 no.2
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• pp.122-129
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• 1997

Ball rolling blending is a popular technique for blending between parametric surfaces. The ball rolling blend surface is conceptually a trajectory of a ball rolling between two base sufaces. It is constructed by sweeping a circular arc along a ball contact curve pair. Since a ball rolling blend surfaces does not have a polynomial form like a Bezier surface patch, it is impossible to apply this method directly to a commercial CAD/CAM system. In this paper an algorithm is developed to approximate a ball rolling blend surface into Bezier surface patches. Least square method is applied to obtain proper Bezier surface patches under a given tolerance. The Bezier surface patches have degree three or more and guarantee VC1-continuity.

• Journal of Korean Society for Quality Management
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• v.38 no.3
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• pp.413-424
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• 2010

Mixture experiments involve combining ingredients or components of a mixture and the response is a function of the proportions of ingredients which is independent of the total amount of a mixture. The purpose of the mixture experiments is to find the optimum blending at which responses such as the flavor and acceptability are maximized. We assume the quadratic or special cubic canonical polynomial model over the experimental region for a mixture since the current mixture is assumed to be located in the neighborhood of the optimal mixture. The cost of the mixture is proportional to the cost of the ingredients of the mixture and is the linear function of the proportions of the ingredients. In this paper, we propose mixture response surface methods to develop a mixture such that the cost is down more than ten percent as well as mean responses are as good as those from the current mixture. The proposed methods are illustrated with the well known the flare experimental data described by McLean and Anderson(1966).

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1996.11a
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• pp.774-778
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• 1996

Developed in this research is a surface modeling kernel for various CAD/CAM applications. Its internal surface representations are rational parametric polynomials, which are generalizations of nonrational Bezier, Ferguson, Coons and NURBS surface, and are very fast in evaluation. The kernel is designed under the OOP concepts and coded in C++ on PCs. The present implementation of the kernel supports surface construction methods, such as point data interpolation, skinning, sweeping and blending. It also has NURBS conversion routines and offers the IGES and ZES format for geometric information exchange. It includes some geometric processing routines, such as surface/surface intersection, curve/surface intersection, curve projection and so forth. We are continuing to work with the kernel and eventually develop a B-Rep based solid modeler.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.2
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• pp.373-381
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• 2009

In this paper, a humanoid robot is simulated and implemented to walk up a staircase using the blending polynomial and genetic algorithm. Using recently developed kinematics for a biped robot, four schemes for walking up a staircase are newly proposed and simulated separately. For the two schemes of landing a swaying leg on the upper stair, the joint trajectories of seven motors are particularly optimized to generate an energy-minimal motion with the guarantee of walking stability. The proposed scheme of walking upstair is validated by an experiment with a small humanoid robot.

• Journal of the Korean Society of Food Science and Nutrition
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• v.35 no.8
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• pp.1051-1056
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• 2006

Response surface methodology was used to investigate the quality of clarified mixed apple and carrot juices using ultrafitration. Apple and carrot juices were blended at the ratio of 1:3, 1:1, and 3:1. A three-variable, three-level central composite design was employed where the independent variables were the blend ratio, temperature and average transmembrane pressure (ATP). With increasing temperature and pressure, flux linearly increased regardless of blending ratio. Blend juice with 75% apple showed the highest soluble sugar and total sugar content in apple and carrot blend juices. Soluble solid contents were more affected by blending ratio than temperature and ATP. Total sugar contents were greatly affected by temperature; increasing temperature led to higher total sugar content up to $25^{\circ}C$. Higher carrot ratio led to higher vitamin C content. In general, higher acidity was achieved by higher apple content and acidity was increased with increasing temperature. Turbidity increased for all samples as APT increased, with the blending ratio of 1:1 (apple:carrot) showing the highest turbidity. Viscosity was greatly changed in the blending ratio of 3:1 (apple:carrot) juice. The polynomial models developed by RSM were satisfactory to describe the relationships between the studied factors and the responses. Analytical optimization gave $flux=0.216\;L/m^2.h$, soluble $solids=10.39^{\circ}Brix$, total sugar=71.32 mg/mL, vitamin C=315.18 mg%, acidity=7.78 mL, turbidity=0.017, and viscosity=1.44 cp, when using a $temperature=44.97^{\circ}C$, ATP=113.57 kPa, and blend ratio=28.50%.

• Journal of Korean Society for Quality Management
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• v.40 no.3
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• pp.347-358
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• 2012

Purpose: Given the mixture components - process variables experimental data, we propose the strategy to find the proper combined model. Methods: Process variables are factors in an experiment that are not mixture components but could affect the blending properties of the mixture ingredients. For example, the effectiveness of an etching solution which is measured as an etch rate is not only a function of the proportions of the three acids that are combined to form the mixture, but also depends on the temperature of the solution and the agitation rate. Efficient designs for the mixture components - process variables experiments depend on the mixture components - process variables model which is called a combined model. We often use the product model between the canonical polynomial model for the mixture and process variables model as a combined model. Results: First we choose the reasonable starting models among the class of admissible product models and practical combined models suggested by Lim(2011) based on the model selection criteria and then, search for candidate models which are subset models of the starting model by the sequential variables selection method or all possible regressions procedure. Conclusion: Good candidate models are screened by the evaluation of model selection criteria and checking the residual plots for the validity of the model assumption. The strategy to find the proper combined model is illustrated with examples in this paper.

• Journal of Korean Society for Quality Management
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• v.39 no.3
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• pp.400-411
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• 2011

Process variables are factors in an experiment that are not mixture components but could affect the blending properties of the mixture ingredients. For example, the effectiveness of an etching solution which is measured as an etch rate is not only a function of the proportions of the three acids that are combined to form the mixture, but also depends on the temperature of the solution and the agitation rate. Efficient designs for the mixture components-process variables experiments depend on the mixture components-process variables model which is called a combined model. We often use the product model between the canonical polynomial model for the mixture and process variables model as a combined model. In this paper we propose three starting models for the mixture components-process variables experiments. One of the starting model we are considering is the model which includes product terms up to cubic order interactions between mixture effects and the linear & pure quadratic effect of the process variables from the product model. In this paper, we propose a method for finding robust designs and practical designs with respect to D-, G-, and I-optimality for the various starting combined models and then, we find practically efficient and robust designs for estimating the regression coefficients for those models. We find the prediction capability of those recommended designs in the case of three components and three process variables to be good by checking FDS(Fraction of Design Space) plots.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.2
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• pp.268-275
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• 2011

This paper proposes two optimal path planning methods of a mobile robot using uDEAS (univariate Dynamic Encoding Algorithm for Searches). Before start of autonomous traveling, a self-controlled mobile robot must generate an optimal global path as soon as possible. To this end, numerical optimization method is applied to real time path generation of a mobile robot with an obstacle avoidance scheme and the basic path generation method based on the concept of knot and node points between start and goal points. The first improvement in the present work is to generate diagonal paths using three node points in the basic path. The second innovation is to make a smooth path plotted with the blending polynomial using uDEAS. Effectiveness of the proposed schemes are validated for several environments through simulation.