• Proceedings of the Korean Society of Precision Engineering Conference
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• 1995.10a
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• pp.315-318
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• 1995

In this paper, an optimal trunk trajectory for stable walking of biped robots is expressed as a simple differential equation, which is then solved by numerical methods. We used ZMP (Zero Moment Point), the virtual total ground reaction point within the region of the supporting food, as the criterion of stability of biped robot walking. If the ZMP is located outside of the stable region in dynamic walking, biped robots fall down. The biped robot considered in this paper consists of two legs and a trunk. The trajectories of the two legs and the ZMP of the biped robot are determined such that they are similar ti those of a human. Based upon those trajectories, the trunk trajectory is solved by numerically integrating differential dynamic equations. Leg motions are controlled by the computed torque control method. The effectiveness of control algorithm as well as the trajectories is confirmed by computer simulations.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.225-230
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• 2003

This paper proposes a desired trajectory and a control algorithm for a biped robot with curved soles. Firstly, we derived the desired trajectory from a model called the Moving Inverted Pendulum Mode (MIPM) of which a contact point of the foot is moving in the horizontal direction. A biped robot with curved soles is under-actuated system, because it has one contact point with the ground during the single supporting phase. Therefore, to solve the under-actuated problem, we changed control variables, used modified dynamic equations and used the computed torque control. The simulation results show that a biped robot with curved soles walks stably. Also, fast walking and natural motion of a biped robot can be implemented.

• Journal of Institute of Control, Robotics and Systems
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• v.12 no.3
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• pp.233-240
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• 2006

This paper presents the robust control method using a self recurrent wavelet neural network (SRWNN) via adaptive backstepping design technique for stable walking of biped robots with unknown model uncertainties. The SRWNN, which has the properties such as fast convergence and simple structure, is used as the uncertainty observer of the biped robots. The adaptation laws for weights of the SRWNN and reconstruction error compensator are induced from the Lyapunov stability theorem, which are used for on-line controlling biped robots. Computer simulations of a five-link biped robot with unknown model uncertainties verify the validity of the proposed control system.

• Journal of the Korean Society of Industry Convergence
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• v.19 no.1
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• pp.1-9
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• 2016

In this paper, we propose a new learning control scheme for various walk motion control of biped robot with same learning-base by neural network. We show that learning control algorithm based on the neural network is significantly more attractive intelligent controller design than previous traditional forms of control systems. A multi layer back propagation neural network identification is simulated to obtain a dynamic model of biped robot. Once the neural network has learned, the other neural network control is designed for various trajectory tracking control with same learning-base. The biped robots have been received increased attention due to several properties such as its human like mobility and the high-order dynamic equation. These properties enable the biped robots to perform the dangerous works instead of human beings. Thus, the stable walking control of the biped robots is a fundamentally hot issue and has been studied by many researchers. However, legged locomotion, it is difficult to control the biped robots. Besides, unlike the robot manipulator, the biped robot has an uncontrollable degree of freedom playing a dominant role for the stability of their locomotion in the biped robot dynamics. From the simulation and experiments the reliability of iterative learning control was illustrated.

• 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.

• 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.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.41-41
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• 2000

biped robots are expected to robustly traverse terrain with various unknown surfaces. The robot will occasionally encounter the unexpected events in made-for human environments. The slipping is a very real and serious problem in the unexpected events. The robot system must respond to the unexpected slipping after it has occurred and before control is lost. This paper proposes a reflex control method for biped robots to recover from slipage. Computer simulations with the 6-DOF environment model which consists of nonlinear dampers, nonlinear springs, and linear springs, show that the proposed method is effective in preventing fall-down due to slippage.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.1157-1160
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• 1996

Control of a biped robot which has compliant ankle joints is dealt in this paper. Simulated version of a human ankle joint is built using springs and mechanical constraints, which gives a flexibility of joint and compliance against the touching ground. The biped robot with compliant ankle joints proposed here gives a good contact between its sole and the ground and makes foot landing soft. As a result, installing force sensors for measuring the center of gravity of the biped becomes easier. A motor to drive an ankle joint is not needed which makes legs light. However, the control problem becomes more difficult because the torque of the ankle joint to put the biped in a desired walking gait cannot be provided from the compliant ankle joint. To solve this problem, we proposed a dynamic gait modification method by adjusting the position of a hip joint. Simulation results for the mathematical model of the SD-2 biped in the Ohio State University are given to show the validity of the proposed controller.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.2279-2284
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• 2005

Generally, biped walking is difficult to control because it is a nonlinear system with various uncertainties. In this paper, we design a robust control system based on sliding-mode control (SMC) of 5-link biped robot using the wavelet neural network(WNN), in order to improve the efficiency of position tracking performance of biped locomotion. In our control system, the WNN is utilized to estimate uncertain and nonlinear system parameters, where the weights of WNN are trained by adaptive laws that are induced from the Lyapunov stability theorem. Finally, the effectiveness of the proposed control system is verified by computer simulations.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.59 no.1
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• pp.29-34
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• 2010

This paper presents an intelligent learning controller for repetitive walking motion of biped walking robot. The proposed learning controller consists of an iterative learning controller and a direct learning controller. In the iterative learning controller, the PID feedback controller takes part in stabilizing the learning control system while the feedforward learning controller plays a role in compensating for the nonlinearity of uncertain biped walking robot. In the direct learning controller, the desired learning input for new joint trajectories with different time scales from the learned ones is generated directly based on the previous learned input profiles obtained from the iterative learning process. The effectiveness and tracking performance of the proposed learning controller to biped robotic motion is shown by mathematical analysis and computer simulation with 12 DOF biped walking robot.