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

• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.33 no.10
• /
• pp.1014-1022
• /
• 2009

A biped robot in locomotion can be regarded to be kinetically redundant in that the link-chain from its foot on the ground to its swing foot has more degrees of freedom that needed to realize stable bipedal locomotion. This paper proposes a new method to generate a trajectory for bipedal locomotion based on this redundancy, which directly generates a locomotion trajectory at the joint level unlike some other methods such as LIPM (linear inverted-pendulum mode) and GCIPM (gravity-compensated inverted-pendulum mode), each of which generates a trajectory of the center of gravity or the hip link under the assumption of the dominance of the hip-link inertia before generating the trajectory of the whole links at the joint level. For the stability of the trajectory generated in the proposed method, a stability condition based on the ZMP (zero-moment point) is used as a constraint as well as other kinetic constraints for bipedal motions. A 6-DOF biped robot is used to show how a stable locomotion trajectory can be generated in the sagittal plane by the proposed method and to demonstrate the feasibility of the proposed method.

• Journal of the Korean Society for Precision Engineering
• /
• v.29 no.4
• /
• pp.417-425
• /
• 2012

This paper presents reference ZMP trajectory generation and implementation for a biped robot via linear inverted dumbbell model (LIDM), which can consider the effect of external momentum on the center of mass (COM) of robot. Based on a reference ZMP trajectory derived by using LIDM, a base trajectory is proposed not only to make the locomotion of robot similar to that of human but also to facilitate its implementation and tuning. In order to realize a dynamic walking using the proposed trajectory, compliance, impedance and ZMP tracking controllers are adopted together. Extensive experiments show that the proposed locomotion of a biped robot is stable and also, similar to that of human. Further researches on balance recovery of a biped robot will be carried out to guarantee its robust locomotion in combination with the proposed trajectory.

• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.34 no.6
• /
• pp.683-693
• /
• 2010

In this paper, we propose a new parallel mechanism for the legs of biped robots and the control of the robot's locomotion. A leg consists of two 3-DOF parallel platforms linked serially: one is an orientation platform for a thigh and the other is the 3-DOF asymmetric parallel platform for the shank. The desired locomotion trajectory is generated on the basis of the Gravity-Compensated Inverted Pendulum Mode (GCIPM) in the sagittal direction and the Linear Inverted Pendulum Mode (LIPM) in the lateral direction, respectively. In order to simulate the ground reaction force, a 6-DOF elastic pad model is used underneath each of the soles. The performance and effectiveness of the proposed parallel mechanism and locomotion control are shown by the results of computer simulations of a 12-DOF parallel biped robot using $SimMechanics^{(R)}$.

• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.24 no.6 s.177
• /
• pp.1513-1519
• /
• 2000

This paper proposes a hybrid control method of using impedance control and the computed-torque control for biped robot locomotion. Computed torque control is used for supporting (constrained) leg. For the free leg, the impedance control is used, where different values of impedance parameters are used depending on the gait phase of the biped robot. To reduce the magnitude of an impact and guarantee a stable footing when a foot contacts with the ground, this paper proposes to increase the damping of the leg drastically and to modify the reference trajectory of the leg. Computer simulations with a 3 -dof environment model for which a combination of a nonlinear and a linear compliant models is used, show that the proposed controller is superior to the computed-torque controllers in reducing impacts and stabilizing the footing.

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

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

• Proceedings of the KIEE Conference
• /
• 2005.10b
• /
• pp.424-426
• /
• 2005

We propose an analytic trajectory planning method using a wavelet neural network (WNN) for a natural and stable locomotion of the 9-link biped robot. We design a appropriate locomotion, which have a kick-action, by means of a ballastic walking model condition. In this paper, a WNN is used to interpolate the trajectory planed by the analytic method. Finally, we show the proposed trajectories through the computer simulation.

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 2011.06a
• /
• pp.297-298
• /
• 2011

• Journal of the Korean Society of Industry Convergence
• /
• v.18 no.4
• /
• pp.259-266
• /
• 2015

This study presents new scheme for various walking pattern of biped robot under the limitted enviroments. We show that the neural network is significantly more attractive intelligent controller design than previous traditional forms of control systems. A multilayer backpropagation neural network identification is simulated to obtain a learning control solution 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 main advantage of our scheme is that we do not require any knowledge about the system dynamic and nonlinear characteristic, and can therefore treat the robot as a black box. It is also shown that the neural network is a powerful control theory for various trajectory tracking control of biped robot with same learning-vase. That is, we do net change the control parameter for various trajectory tracking control. Simulation and experimental result show that the neural network is practically feasible and realizable for iterative learning control of biped robot.