• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1993년도 한국자동제어학술회의논문집(국내학술편); Seoul National University, Seoul; 20-22 Oct. 1993
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• pp.889-894
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• 1993

This paper presents a robust adaptive control scheme based on the Lyapunov design for robot manipulators subjected to inertial parameter uncertainties and bounded torque disturbances. The scheme is a modified version of the adaptive computed torque method which adopts a dead zone into the adaptation mechanism so as to avoid parameter drifts by disturbances. It is shown via stability analysis and computer simulations that all the signals in the overall adaptive system are bounded and tracking errors lie within a prespecified bound.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2005년도 ICCAS
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• pp.1456-1459
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• 2005

To compensate the drawbacks, a new localization method that estimates the global position of the mobile robot by using a camera set on ceiling in the corridor is proposed. This scheme is not a relative localization, which decreases the position error through algorithms with noisy sensor data. The effectiveness of the proposed localization scheme is demonstrated by the experiments.

• 제어로봇시스템학회논문지
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• 제17권12호
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• pp.1256-1265
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• 2011

Automated parking assist systems are being commercialized and rapidly spread in the market. In order to improve odometry accuracy, we proposed a practical odometry calibration scheme of Car-Like Mobile Robot (CLMR). However, there were some open problems in our prior work. For example, it was not clear whether the kinematic parameters always converged or not using the proposed calibration scheme. In addition, test driving had to be carried out "twice" without detailed explanation. This research aims to provide answers for the addressed questions though the convergence property analysis of the calibration scheme. In this paper, we evaluate on the effect of the kinematic parameter error on the odometry error at the final pose by numerical computation. The evaluation will show that the wheel diameter and tread of the CLMR can be calibrated by iterative test drives. In addition, the region of convergence in the parametric space will be discussed. Presented experimental results clearly showed that the proposed calibration scheme would be useful in practical applications.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1988년도 한국자동제어학술회의논문집(국내학술편); 한국전력공사연수원, 서울; 21-22 Oct. 1988
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• pp.45-49
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• 1988

This paper presents a centralized adaptive control scheme based on perturbation equations in the vicinity of a desired trajectory,which are used to design a feedback control about the desired trajectory. This adaptive control scheme reduces the manipulator control problem from a nonlinear control to controlling a linear control system about a desried trajectory. Computer simulation studies of a two-joint manipulator are performed on a IBM-PC to illustrate the performance of this adaptive control scheme.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1990년도 한국자동제어학술회의논문집(국제학술편); KOEX, Seoul; 26-27 Oct. 1990
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• pp.1167-1172
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• 1990

This paper discusses a force distribution scheme which minimizes the weighted norm of the forces/torques applied on weak points of cooperating multiple robot arms. The scheme is proposed to avoid the damage or unwanted motion of any weak point of robots or object stemming from excessive forces/torques. Since the proposed scheme can be used for either the joint torque minimization or the exerted force minimization on the object, it can be regarded as a unified force minimization method for multiple robot arms. The computational complexity in this scheme is analyzed using the properties of Jarcobian. Simulation of two identical PUMA robots held an object is carried out to illustrate the proposed scheme. By the proper choice of the weighting matrix in the performance index, we show that force minimization for a weak point can be achieved, and that the exerted force minimization on the object can be changed to the joint torque minimization.

• 제어로봇시스템학회논문지
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• 제11권6호
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• pp.524-529
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• 2005

In this paper, a novel neural network compensation technique for PD like fuzzy controlled robot manipulators is presented. A standard PD-like fuzzy controller is designed and used as a main controller for controlling robot manipulators. A neural network controller is added to the reference trajectories to modify input error space so that the system is robust to any change in system parameter variations. It forms a neural-fuzzy control structure and used to compensate for nonlinear effects. The ultimate goal is same as that of the neuro-fuzzy control structure, but this proposed technique modifies the input error not the fuzzy rules. The proposed scheme is tested to control the position of the 3 degrees-of-freedom rotary robot manipulator. Performances are compared with that of other neural network control structure known as the feedback error learning structure that compensates at the control input level.

• 제어로봇시스템학회논문지
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• 제6권6호
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• pp.471-477
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• 2000

The position control accuracy of a robot arm is significantly deteriorated when a long arm robot is operated at a high speed. In this case, the robot arm must be modeled as a flexible structure, not a rigid one, and its control system should be designed with its elastic modes taken into account. In this paper, the tip position control scheme of a one-link flexible manipulator using 2-DOF controller with sliding mode is presented. The robot consists of a flexible arm manufactured with a thin aluminium plate, an AC servo motor with a harmonic drive for speed reduction, an optical encoder and a CCD camera as a vision sensor for on-line measuring the tip deflection of the flexible m. Simulation and experimental results of the flexible manipulator with a proposed controller are provided to show the effectiveness of the controller.

• 제어로봇시스템학회논문지
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• 제11권4호
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• pp.330-336
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• 2005

An intelligent control method is proposed for control of rigid robot manipulators which achieves exponential tracking of repetitive robot trajectory under uncertain operating conditions such as parameter uncertainty and unknown deterministic disturbance. In the learning controller, exponentially stable learning algorithms are combined with stabilizing computed error feedforward and feedback inputs. It is shown that all the error signals in the learning system are bounded and the repetitive robot motion converges to the desired one exponentially fast with guaranteed convergence rate. An engineering workstation based control system is built to verify the effectiveness of the proposed control scheme.

• 전기학회논문지P
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• 제55권2호
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• pp.83-88
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• 2006

This paper proposes a method that minimizes the consumed energy by searching the optimal locations of the mass centers of the biped robot's links using Genetic Algorithm. This paper presents a learning controller for repetitive gait control of the biped robot. The learning control scheme consists of a feedforward learning nile and linear feedback control input for stabilization of learning system. The feasibility of learning control to the biped robotic motion is shown via computer simulation and experimental results with 24 DOF biped walking robot.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2008년도 추계학술대회A
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• pp.735-738
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• 2008

A 6 D.O.F Stewart platform type parallel robot has been developed as a simulator to test the surveillance robot stabilization control. Since the surveillance robot is installed on the unmanned ground vehicle (UGV), it is required to have a stabilization control system to compensate the disturbance from the UGV. PID control scheme has been applied to the parallel robot to generate controlled motion following the input motion.