• Proceedings of the KIEE Conference
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• 2006.10c
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• pp.539-541
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• 2006

Biped locomotion is a popular research area in robotics due to the high adaptability of a walking robot in an unstructured environment. When attempting to automate the motion planning process for a biped walking robot, one of the main issues is assurance of dynamic stability of motion. This can be categorized into three general groups: body stability, body path stability, and gait stability. A zero moment point (ZMP), a point where the total forces and moments acting on the robot are zero, is usually employed as a basic component for dynamically stable motion. In this rarer, learning based neuro-fuzzy systems have been developed and applied to model ZMP trajectory of a biped walking robot. As a result, we can provide more improved insight into physical walking mechanisms.

• Proceedings of the KIEE Conference
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• 2001.11c
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• pp.301-303
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• 2001

This paper deals with the biped robot gait on changing the initial postures. Gait of a biped robot depends on the constraints of mechanical kinematics and initial posture. Also biped robot's dynamic walking stability is investigated by ZMP(Zero Moment Point). The path trajectory. with the knee joint bent like a human, is generated and applied with the above considerations. To decrease trajectory tracking error, in this paper, a new initial posture similar to bird's case is proposed and realized with the real robot.

• Proceedings of the KIEE Conference
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• 2004.07d
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• pp.2438-2440
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• 2004

This study is concerned with development of 3-Dimensional simulator of a biped robot that has a prismatic balancing weight or a revolute balancing weight. The dynamic stability equation of a biped robot which have a prismatic balancing weight is conditional linear but a walking robot's stability equation with a revolute balancing weight is nonlinear. To get a stable gait of a biped robot, stabilization equations with ZMP (Zero Moment Point) are modeled as non-homogeneous second order differential equations for each balancing weight type. A trajectory of balancing weight can be directly calculated with the FDM (Finite Difference Method) solution of the linearized differential equation. In this paper, the 3-Dimensional graphic simulator is programmed to get and calculate the desired ZMP and the actual ZMP. Walking of 4 steps was simulated and verified. This balancing system will be applied to a biped humanoid robot, which consist Begs and upper body, at future work.

• Proceedings of the IEEK Conference
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• 2008.06a
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• pp.1059-1060
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• 2008

In this paper, using a genetic algorithm, consisting of six to seven degrees of freedom links, walking robot to up-stair that can walk to optimize energy and stability to generate. Walking robot to up-stairs of the four-step segmentation of the various situations that match the pace and pattern so that it can generate. It also generated using genetic algorithms to test for Matlab into the Robot Simulation of the humanoid experiment was used.

• Proceedings of the KIEE Conference
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• 2006.04a
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• pp.312-314
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• 2006

Researches on biped robot walking have been mostly focusing on walking on even surfaces. Therefore, robot walking has been only realized on pre-specified spaces with pre-specified movements according to the previous researches. In this paper a walking system for a biped robot using fuzzy system and neural networks to overcome those constraints. The system enables biped walking to be possible in various environments and with more complicated obstacels. For the purpose, a walking robot should recognize its surrounding environment and determine its movement. In the proposed system, a robot dynamically generates its walking trajectories of each joint by using neural networks when facing new obstacle such as stairs, and it maintains its walking stability by using closed loop fuzzy control system which manipulates the waist joints.

• Proceedings of the KIEE Conference
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• 2002.11c
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• pp.169-172
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• 2002

This paper is concerned with walking trajectory generation by applying the genetic algorithm. The walking trajectory is generated though three via-points and genetic algorithm is employed to find velocity and acceleration at each via-point. Also genetic algorithm is applied for balancing joint trajectory. Fitness function is used for minimizing the trajectory. As a result, new algorithm generated the smooth trajectory. The proposed algorithm is verified by the experiment of biped walking robot developed in our Control laboratory, and we compared the result with the previous walking algorithm. It showed that the new proposed algorithm generated the better walking trajectory.

• Proceedings of the KIEE Conference
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• 2002.07d
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• pp.2433-2435
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• 2002

The purpose of this paper is to introduce a case study of developing a miniature biped robot. The biped robot has a total of twenty-one degrees of freedom(DOF) ; There are two legs which have six DOF each, two arms which have three DOF each and a waist which has three DOF. RC servo-motors were used as actuators. We have developed motor controller, sensor controller and ISA-interface card. Motor controller, PWM generator, can control eight motors Sensor controller is connected to eight FSR(Force Sensing Resistors). For high level controller communicate with low level controller, ISA-interface card has developed. For the stable walking, CMAC(Cerebellar Model Articulation Controller) neural network algorithm is applied to our system CMAC is robust at noise.

• 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.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.56 no.4
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• pp.161-167
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• 2007

This paper introduces a dynamic walking control of biped walking robot using intelligent sensor interface and shows an intelligent control method for biped walking robot. For the dynamic walking control of biped walking robot, serious motion controllers are used. They are main controller(using INTEL80C296SA MPU), sub controller(using TMS320LF2406 DSP), sensor controller(using Atmega128 MPU) etc. The used sensors are gyro sensor, tilt sensor, infrared sensor, FSR sensor etc. For the feasibility of a dynamic walking control of biped walking robot, we use the biped walking robot which has twenty-five degrees of freedom(D.O.F.) in total. Our biped robot is composed of two legs of six D.O.F. each, two arms of five D.O.F. each, a waist of two D.O.F., a head of one D.O.F.

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.2804-2807
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• 2000

This paper suggests a method of the forward dynamic analysis for the computer simulation on the analysis of the dynamic behavior for biped walking robot. The equations f motion of the system or the simulation are constructed by using the Method of the multibody dynamics which is powerful method for modeling of the complex biped system. For the simplicity of simulation, we consider that the sole of the contacting foot is affected by the reaction forces for tree structure system topology instead of the addition or deletion of the kinematic constraints. The ground reaction forces can be modeled using the simple spring and damper model at the three contacting points on the sole of the foot. For minimizing the errors of numerical integration, the number of equations of motion is minimized by adding the driving constraints or a controller instead of the direct driving torques.