• Proceedings of the KIEE Conference
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• 1989.07a
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• pp.675-678
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• 1989

This paper proposes two types of the preview algorithms to predict the joint velocities and joint positions, and deals with a control approach using the preview algorithms for the precise trajectory control. Specifically, a predictor an the form of discrete time state equations is proposed based on the robot dynamics model linearized by the computed torque method. And another state predictor is proposed by the beat line fitting in the least square sense, where present joint velocities and positions and several past positions are employed. Then computer simulations are performed for the SCARA robot with two d.o.f. to show the validities of the proposed algothrithms.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.67.3-67
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• 2001

A fuzzy control strategy is described which is utilized to control the joint angle and tip deflection in single flexible manipulator. In this paper, an existing model for a single flexible manipulator is used f3r the initial development of an FLC. One FLC is designed to govern the joint angle of the manipulator as it is rotated from one position to another, and a second FLC is designed to attenuate the tip deflection which result from joint angle body motion. Reference Trajectory Command is an important method to reduce vibration in flexible beam. This paper presents a very simple command control shaping which eliminates multiple mode residual vibration in a flexible beam combined fuzzy controller ...

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.474-474
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• 2000

This paper shows that a system with two-link arm can obtain hand reaching movement to a target object projected on a visual sensor by reinforcement learning using a layered neural network. The reinforcement signal, which is an only signal from the environment, is given to the system only when the hand reaches the target object. The neural network computes two joint torques from visual sensory signals, joint angles, and joint angular velocities considering the urn dynamics. It is known that the trajectory of the voluntary movement o( human hand reaching is almost straight, and the hand velocity changes like bell-shape. Although there are some exceptions, the properties of the trajectories obtained by the reinforcement learning are somewhat similar to the experimental result of the human hand reaching movement.

• Journal of the Korea Institute of Military Science and Technology
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• v.10 no.3
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• pp.161-172
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• 2007

This article suggests an inverse kinematics analysis of a two degree of freedom spatial parallel motion simulator and design methodology of the robust PID controller. The parallel motion simulator consists of a fixed base and a moving frame connected by two serial chains, with each serial chain containing one revolute joint and two passive spherical joint. First, an inverse kinematics problems are solved in order to find the joint variable necessary to bring the end effector to track the desired trajectory. Second, an inverse optimal PID controller is proposed to track trajectories in the face of uncertainty. And the $H_{\infty}$ optimality and robust stability of the closed-loop system is acquired through the PID controller. Finally numerical results show the effectiveness of the PID controller that is designed by square/linear tuning laws.

• The Journal of Korea Robotics Society
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• v.6 no.4
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• pp.301-307
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• 2011

Based on the stability criteria of ZMP (Zero Moment Point), this paper proposes an adjusting algorithm that modifies walking trajectory of a bipedal robot for stable walking by analyzing ZMP trajectory of it. In order to maintain walking balance of the bipedal robot, ZMP should be located within a supporting polygon that is determined by the foot supporting area with stability margin. Initially tilting imposed to the trajectory of the upper body is proposed to transfer ZMP of the given walking trajectory into the stable region for the minimum stability. A neural network method is also proposed for the stable walking trajectory of the biped robot. It uses backpropagation learning with angles and angular velocities of all joints with tilting to get the improved walking trajectory. By applying the optimized walking trajectory that is obtained with the neural network model, the ZMP trajectory of the bipedal robot is certainly located within a stable area of the supporting polygon. Experimental results show that the optimally learned trajectory with neural network gives more stability even though the tilting of the pelvic joint has a great role for walking stability.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.20 no.4
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• pp.386-394
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• 2011

This paper is concerned with the application of the vision control scheme for robot's point placement task in discontinuous trajectory caused by obstacle. The proposed vision control scheme consists of four models, which are the robot's kinematic model, vision system model, 6-parameters estimation model, and robot's joint angles estimation model. For this study, the discontinuous trajectory by obstacle is divided into two obstacle regions. Each obstacle region consists of 3 cases, according to the variation of number of cameras that can not acquire the vision data. Then, the effects of number of cameras on the proposed robot's vision control scheme are investigated in each obstacle region. Finally, the practicality of the proposed robot's vision control scheme is demonstrated experimentally by performing the robot's point placement task in discontinuous trajectory by obstacle.

• Journal of Institute of Control, Robotics and Systems
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• v.8 no.10
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• pp.890-897
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• 2002

This paper deals with the reduction of trajectory tracking error by changing the initial postures of a biped robot. Gait of a biped robot depends on the constraints of mechanical kinematics and the initial states including the posture. Also the dynamic walking stability in a biped robot system is analyzed by zero moment point(ZMP) among the stabilization indices. Path trajectory, in which knee joint is bent forward like human's cases, is applied to most cases considered with above conditions. A new initial posture, which is similar to bird's gait, is proposed to decrease trajectory tracking error and it is verified through real experimental results.

• ETRI Journal
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• v.40 no.5
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• pp.653-663
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• 2018

Patients with spinal cord injuries cannot move their limbs using their intact muscles. A suitable controller can be used to move their arms by employing the functional electrical stimulation method. In this article, a fuzzy exponential sliding-mode controller is designed to move a musculoskeletal human arm model to track an optimal trajectory in the sagittal plane. This optimal arm trajectory is obtained by developing a policy for the central nervous system. In order to specify the optimal trajectory between two points, two dynamic and static optimal criteria are applied simultaneously. The first dynamic objective function is defined to minimize the joint torques, and the second static optimization is offered to minimize the muscle forces at each moment. In addition, fuzzy logic is used to tune the sliding-surface parameter to enable an appropriate tracking performance. Simulation results are evaluated and compared with experimental data for upward and downward movements of the human arm.

• Journal of the Korea Convergence Society
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• v.11 no.5
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• pp.175-182
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• 2020

The calculation of the optimal trajectory of the stepped top-down robot was made using a genetic algorithm and a computational torque controller. First, the total energy efficiency was minimized using the Red-Cold Generic Algorithm (RCGA) consisting of reproductive, cross, and mutation. The reproducibility condition related to the position assembly of the start and end of the stride and the joints, angles, and angular velocities are linear constraints. Next, the unequal constraint accompanies the condition for preventing the collision of the swing leg at the corner with the outer surface of the stairs, the condition of the knee joint for preventing kinematic peculiarity, and the condition of no moment in safety in the traveling direction. Finally, the angular trajectory of each joint is defined by fourth-order polynomial whose coefficient is to approximate chromosomes. This is to approximate walking. In this study, the energy efficiency of the optimal trajectory was analyzed by computer simulation through a biped robot with seven degrees of freedom composed of seven links.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.42 no.3 s.303
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• pp.1-10
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• 2005

This paper proposes a novel fault-tolerant gait planning of a hexapod robot considering kinematic constraints. The failure concerned in this paper is a locked joint failure for which a joint in a leg cannot move and is locked in place. It is shown that the conventional fault-tolerant gait of a hexapod robot for forward walking on even terrain may be fallen into deadlock, depending on the configuration of the failed leg. For coping with such deadlock situation, a novel fault-tolerant gait planning is proposed. It can avoid deadlock by adjusting the position of the foot trajectory, and has the same leg sequence and stride length as those of the conventional fault-tolerant gait. To demonstrate the superiority of the proposed scheme, a case study is presented in which a hexapod robot, having walked over even terrain before a locked joint failure, could avoid deadlock and continue its walking by the proposed fault-tolerant gait planning.