• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1934-1937
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• 2005

This paper proposes suitable gait generation for dynamic walking of biped robot with varying load in real time. Author proposes the relationship between ZMP(Zero Moment Point) and measurement from FSR(Force Sensing Register). Simplifying this relationship, it is possible to reduce the computational time and control the biped robot in real time. If the weight of the biped robot varies in order to move some object, then joint trajectories of the the biped robot must be changed. When some object is loaded on the biped robot in it's home position, FSRs can measure the variation of weight. Evaluating the relations between varying load and stable gait of the biped robot, it can walk adaptively. This relation enables the biped robot to walk properly with varying load. The simulation is also represented in this paper which shows proposed relationships.

• Proceedings of the KIEE Conference
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• 2006.10c
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• pp.570-572
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• 2006

This paper discusses the method of moving object detection for biped robot walking. Most researches on vision based object detection have mostly focused on fixed camera based algorithm itself. However, developing vision systems for biped walking robot is an important and urgent issue since hired walking robots are ultimately developed not only for researches but to be utilized in real life. In the research, method for moving object detection has been developed for task assignment and execution of biped robot as well as for human robot interaction (HRI) system. But these methods are not suitable to biped walking robot. So, we suggest the advanced method which is suitable to biped walking robot platform. For carrying out certain tasks, an object detecting system using modified optical flow algorithm by wireless vision camera is implemented in a biped walking robot.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1995.10a
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• pp.311-314
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• 1995

Biped locomotion can be simply modeled as a linear inverted pendulum mode. This model considers only the CG (center of gravity) of the entire system. But in real biped robot systems, the free-leg motion dynamics is not negligible. So if its dynamics is not considered in designing the reference CG motion, it is badly influence to the ZMP(zero moment point) position of the biped robot walking in the sagittal plane. Therefore, we modeled the biped locomotion similar to the linear inverted pendulum mode but considered the predetermined free-leg dynamics. To verify that the proposed biped locomotion is more stable than the linear inverted pendulum mode, we constructed a biped robot simulator and designed a serco controller to track both the reference motion of the free leg and the reference motion of CG of the biped robot using the computed torque control low. And through simulations, we verified that the proposed walking is better in stability than the one based on the linear inverted pendulum mode.

• 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.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.538-538
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• 2000

This paper presents a learning controller for repetitive gate control of biped robot. The learning control scheme consists of a feedforward learning rule and linear feedback control input for stabilization of learning system. The feasibility of teaming control to biped robotic motion is shown via dynamic simulation with 12 dof biped robot.

• Proceedings of the IEEK Conference
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• 2003.07c
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• pp.2573-2576
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• 2003

This paper proposes the controller for biped robot using intelligent control algorithm. The main purpose of this paper is to design the robot controller using Hierarchical Mixture of Experts(HME). The neural network direct control method will be applied to the control scheme for the biped robot and neural network will learn the dynamics of biped robot. The teaming scheme using a intelligent controller to biped robot is developed. The teaming scheme uses a HME controller combined with a inverse biped robot model. The controller provides the control signals at each control time instant. Simulation results are reported for a seven-link biped robot.

• Proceedings of the KIEE Conference
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• 2006.04a
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• pp.123-125
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• 2006

This paper discusses the method of vision based sensor fusion system for biped robot walking. Most researches on biped walking robot have mostly focused on walking algorithm itself. However, developing vision systems for biped walking robot is an important and urgent issue since biped walking robots are ultimately developed not only for researches but to be utilized in real life. In the research, systems for environment recognition and tole-operation have been developed for task assignment and execution of biped robot as well as for human robot interaction (HRI) system. For carrying out certain tasks, an object tracking system using modified optical flow algorithm and obstacle recognition system using enhanced template matching and hierarchical support vector machine algorithm by wireless vision camera are implemented with sensor fusion system using other sensors installed in a biped walking robot. Also systems for robot manipulating and communication with user have been developed for robot.

• Journal of the Korean Society for Precision Engineering
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• v.21 no.7
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• pp.115-123
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• 2004

This paper deals with the gait optimization of via points on biped robot. ZMP(Zero Moment point) is the most important index in a biped robot's dynamic walking stability. To stable walking of a biped robot, leg's trajectory and a desired ZMP trajectory is required, balancing motion is solved by FDM(Finite Difference Method). In this paper, optimal index is defined to dynamically stable walking of a biped robot, and genetic algorithm is applied to optimize gait trajectory and balancing motion of a biped robot. By genetic algorithm, the index of walking parameter is efficiently optimized, and dynamic walking stability is verified by ZMP verification equation. Genetic algorithm is only applied to balancing motion, and is totally applied to whole trajectory. All of the suggested motions of biped robot are investigated by simulations and verified through the real implementation.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1464-1468
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• 2004

This paper presents a learning controller for repetitive gait control of biped walking robot. We propose the iterative learning control algorithm which can learn periodic nonlinear load change ocuured according to the walking period through the iterative learning, not calculating the complex dynamics of walking robot. The learning control scheme consists of a feedforward learning rule and linear feedback control input for stabilization of learning system. The feasibility of learning control to biped robotic motion is shown via dynamic simulation with 12-DOF biped walking robot.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.2
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• pp.148-155
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• 2008

This paper proposes a method of adaptively generating a gait pattern of biped robot. The gait synthesis is based on human's gait pattern analysis. The proposed method can easily be applied to generate the natural and stable gait pattern of any biped robot. To analyze the human's gait pattern, sequential images of the human's gait on the sagittal plane are acquired from which the gait control values are extracted. The gait pattern of biped robot on the sagittal plane is adaptively generated by a genetic algorithm using the human's gait control values. However, gait trajectories of the biped robot on the sagittal plane are not enough to construct the complete gait pattern because the biped robot moves on 3-dimension space. Therefore, the gait pattern on the frontal plane, generated from Zero Moment Point (ZMP), is added to the gait one acquired on the sagittal plane. Consequently, the natural and stable walking pattern for the biped robot is obtained, as proved by the experiments.