• Journal of the Korean Society for Precision Engineering
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• v.30 no.1
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• pp.85-95
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• 2013

As the conventional hydraulic power steering system in the passenger vehicles is being rapidly replaced by EPS (Electric Power Steering) system, performance evaluation of the EPS system has become an important issue in the automotive industries. But the evaluation process takes significant expertise since steering conditions in the test protocols must be implemented with high accuracy. EPS HILS (Hardware-In the-Loop Simulation) system is developed together with robot steering system in this study. Main components of EPS HILS system include: C-EPS hardware, CarSim vehicle model, and road reaction force generation system powered by servo motor. The robot steering system, operated by another servo motor, was combined with EPS HILS system to substitute for steering efforts of human driver. The road reaction force generation system and the robot steering system were carefully validated by using the data obtained from vehicle tests. An on-center handling test was conducted by using EPS HILS system combined with the robot steering system. In the result of this study, robot-steered EPS HILS system developed with its high reliability and no need of skilled driver's, can be widely adopted to evaluate any performance of EPS system.

• Journal of Korea Society of Industrial Information Systems
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• v.19 no.5
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• pp.57-68
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• 2014

MSRDS(Microsoft Robotics Developer Studio), the robot simulation platform provides the simulation robots and environments enabling to the basic robot programming without hardware robots. In this paper, we carry the maze escaping problems to compare and analyze the performance of LRF, bumper, IR, and sonar sensor with the same condition on MSRDS(Microsoft Robotics Developer Studio) environment. To evaluate the performance of sensors, we program the simulation environments with same conditions for all sensors. We could find that the LRF sensor had the highest performance and the bumper sensor has the lowest performance on the travel time, the number of turning, and the number of collisions. It was also confirmed that IR sensor and sonar sensor had lower performance than LRF sensor on the number of turning.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.12
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• pp.1238-1245
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• 2014

This paper proposes an RBFN-based adaptive tracking controller for an electrically driven mobile robot with parametric uncertainties and external disturbances. A mobile robot model considered in this paper includes all models of the robot body and actuators with uncertain kinematic and dynamic parameters, and uncertain frictions and external disturbances. The proposed controller consists of an RBFN(Radial Basis Function Network) and a robust adaptive controller. The presented RBFN is used to approximate unknown nonlinear robot dynamic functions. The proposed controller is adjusted by the adaptation laws obtained through the Lyapunov stability analysis. The proposed control scheme does not a priori need the accurate knowledge of all parameters in the robot kinematics, robot dynamics and actuator dynamics. Also, nominal parameter values are not required in the controller. The global stability of the closed-loop robot control system is guaranteed using the Lyapunov stability theory. Simulation results show the validity and robustness of the proposed control scheme.

• Journal of the Society of Naval Architects of Korea
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• v.49 no.5
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• pp.400-409
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• 2012

It is not easy to know the accurate mass and mass moment of inertia of robot. Because of this uncertainty, error may exist when we control the robot based on the inaccurate mass information. Moreover the properties of the portable robot can change during its operation. Therefore we developed the motion simulator based on the adaptive control. First, the computed torque control was carried out in order to minimize an error between target angles and real angles. The computed torque control is based on the equation of robot motion, which is derived from the Lagrange-Euler equation. To minimize the error between the real model and the approximated model, the adaptive control was carried out. During this simulation, the interference check was also carried out. The interference check verifies that the robot can move successfully without any collision.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.5
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• pp.398-405
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• 2005

The intelligent robots that will be needed in the near future are human-friendly robots that are able to coexist with humans and support humans effectively. To realize this, robots need to recognize their position and posture in known environment as well as unknown environment. Moreover, it is necessary for their localization to occur naturally. It is desirable for a robot to estimate of his position by solving uncertainty for mobile robot navigation, as one of the best important problems. In this paper, we describe a method for the localization of a mobile robot using image information of a moving object. This method combines the observed position from dead-reckoning sensors and the estimated position from the images captured by a fixed camera to localize a mobile robot. Using a priori known path of a moving object in the world coordinates and a perspective camera model, we derive the geometric constraint equations which represent the relation between image frame coordinates for a moving object and the estimated robot's position. Also, the control method is proposed to estimate position and direction between the walking human and the mobile robot, and the Kalman filter scheme is used for the estimation of the mobile robot localization. And its performance is verified by the computer simulation and the experiment.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.54 no.6
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• pp.376-382
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• 2005

In this paper, practical biped humanoid robot is presented, designed, and modeled by fuzzy system. The humanoid robot is a popular research area in robotics because of the high adaptability of a walking robot in an unstructured environment. But owing to the lots of circumstances which have to be taken into account it is difficult to generate stable and natural walking motion in various environments. As a significant criterion for the stability of the walk, ZMP (zero moment point) has been used. If the ZMP during walking can be measured, it is possible for a biped humanoid robot to realize stable walking by a control method that makes use of the measured ZMP. In this study, measuring the ZMP trajectories in real time situations throughout the whole walking phase on the flat floor and slope are conducted. And the obtained ZMP data are modeled by fuzzy system to explain empirical laws of the humanoid robot. By the simulation results, the fuzzy system can be effectively used to model practical humanoid robot and the acquired trajectories will be applied to the humanoid robot for the human-like walking motions.

• Journal of the Korean Institute of Intelligent Systems
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• v.12 no.4
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• pp.289-293
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• 2002

Learning Classifier System (LCS) finds a new rule set using genetic algorithm (GA). In this paper, The Zeroth Level Classifier System (ZCS) is applied to evolving the strategy of a robot soccer simulation game (SimuroSot), which is a state varying dynamical system changed over time, as GBML (Genetic Based Machine Learning) and we show the effectiveness of the proposed scheme through the simulation of robot soccer.

• Journal of Advanced Navigation Technology
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• v.14 no.1
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• pp.57-65
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• 2010

In this paper, we propose the structure of heterogeneous multiprocessor's concept, which is the structure of the new type of the robot controller, and we introduce an integrating structure method, which is distributed multiprocessor within controller using sRIO. We also perform the computer simulation with using the sRIO IP core which was designed within FPGA as the method for implementation of integrated heterogeneous multiprocessor by sRIO communication. Thus, we verify the result.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.912-915
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• 1996

The computed-torque method (CTM) shows good trajectory tracking performance in controlling robot manipulator if there is no disturbance or modelling errors. But with the increase of a payload or the disturbance of a manipulator, the tracking errors become large. So there have been many researches to reduce the tracking error. In this paper, we propose a new control algorithm based on the CTM that decreases a tracking error by generating new reference trajectory to the controller. In this algorithm we used the concept of sliding mode theory and fuzzy system to reduce chattering in control input. For the numerical simulation, we used a 2-link robot manipulator. To simulate the disturbance due to a modelling uncertainty, we added errors to each elements of the inertia matrix and the nonlinear terms and assumed a payload to the end-effector. In this simulation, proposed method showed better trajectory tracking performance compared with the CTM.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.21 no.5
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• pp.756-768
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• 1997

In order to control a dynamic gait of quadrupedal walking robot, the equations of motion of the whole mechanism are required. In this research, the equations of motion are formulated analytically using Kane's dynamic approach. As a dynamic gait model, a trot gait has been adopted. The degree of freedom of whole mechanism could be reduced to 7 by idealizing the kinematic feature of the trot gait. Using the equations of motion formulated, the results of the redundant-joint torque analysis and the simulation of dynamic walking motion are presented.