• 제어로봇시스템학회논문지
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• 제13권7호
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• pp.664-670
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• 2007

This study deals with image-based visual servoing for automatic recharging of mobile robot. Because mobile robot must be recharged periodically, it is necessary to detect and move to docking station. Generally, laser scanner is used for detect of position of docking station. CCD Camera is also used for this purpose. In case of using cameras, the position-based visual servoing method is widely used. But position-based visual servoing method requires the accurate calibration and it is hard and complex work. Another method using cameras is image-based visual servoing. Recently, image based visual servoing is widely used for robotic application. But it has a problem that cannot have linear trajectory in the 3-dimensional space. Because of this weak point, image-based visual servoing has a limit for real application. In case of 2-dimensional movement on the plane, it has also similar problem. In order to solve this problem, we point out the main reason of the problem of the resolved rate control method that has been generally used in the image-based visual servoing and we propose an image-based visual servoing method that can reduce the curved trajectory of mobile robot in the cartesian space.

• International Journal of Control, Automation, and Systems
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• 제4권5호
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• pp.545-558
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• 2006

In this paper, PD-like visual servoing is modified in two ways: a sliding-mode observer is applied to estimate the joint velocities, and a RBF neural network is used to compensate the unknown gravity and friction. Based on Lyapunov method and input--to-state stability theory, we prove that PD-like visual servoing with the sliding mode observer and the neuro compensator is robust stable when the gain of the PD controller is bigger than the upper bounds of the uncertainties. Several simulations are presented to support the theory results.

• 한국정밀공학회지
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• 제20권10호
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• pp.82-88
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• 2003

Many visual servoing algorithms have been recently developed by the robot vision researchers. They do not, however, consider the stability of servoing system. The camera calibration is the most important factor to the control stability and performance of position based visual servoing. In this article we describe the ECL(End Point Closed Loop) servoing can make no steady state error for the control of 6-DOF robot of which accuracy is dependent on the camera calibration and kinematics. And we propose a dynamic calibration algorithm, which can improve stability and performance of ECL visual servoing. To verify the potential of our approach, we run assembly experiments and present our finding.

• 제어로봇시스템학회논문지
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• 제21권8호
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• pp.781-787
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• 2015

This paper proposes a hybrid visual servoing algorithm for the object tracking by a mobile robot with the stereo camera. The mobile robot with the stereo camera performs an object recognition and object tracking using the SIFT and CAMSHIFT algorithms for the hybrid visual servoing. The CAMSHIFT algorithm using stereo camera images has been used to obtain the three-dimensional position and orientation of the mobile robot. With the hybrid visual servoing, a stable balance control has been realized by a control system which calculates a desired angle of the center of gravity whose location depends on variations of link rotation angles of the manipulator. A PID controller algorithm has adopted in this research for the control of the manipulator since the algorithm is simple to design and it does not require unnecessary complex dynamics. To demonstrate the control performance of the hybrid visual servoing, real experiments are performed using the mobile manipulator system developed for this research.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1997년도 한국자동제어학술회의논문집; 한국전력공사 서울연수원; 17-18 Oct. 1997
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• pp.712-715
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• 1997

In image jacobian based visual servoing, generally, inverse jacobian should be calculated by complicated coordinate transformations. These are required excessive computation and the singularity of the image jacobian should be considered. This paper presents a visual servoing to control the pose of the robotic manipulator for tracking and grasping 3-D moving object whose pose and motion parameters are unknown. Because the object is in motion tracking and grasping must be done on-line and the controller must have continuous learning ability. In order to estimate parameters of a moving object we use the kalman filter. And for tracking and grasping a moving object we use a fuzzy inference based reinforcement learning algorithm of dynamic recurrent neural networks. Computer simulation results are presented to demonstrate the performance of this visual servoing

• Journal of Mechanical Science and Technology
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• 제14권7호
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• pp.782-788
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• 2000

In this paper, we present a new approach to visual feedback control using image-based visual servoing with stereo vision. In order to control the position and orientation of a robot with respect to an object, a new technique is proposed using binocular stereo vision. The stereo vision enables us to calculate an exact image Jacobian not only around a desired location but also at other locations. The suggested technique can guide a robot manipulator to the desired location without providing a priori knowledge such as the relative distance to the desired location or the model of an object even when the initial positioning error is large. This paper describes a model of stereo vision and how to generate feedback commands. The performance of the proposed visual servoing system is illustrated by experimental results and compared with conventional control methods for an assembly robot.

• 제어로봇시스템학회논문지
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• 제11권5호
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• pp.411-417
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• 2005

In this study, stereo vision system is applied to a mobile manipulator for effective tasks. The robot can recognize a target and compute the potion of the target using a stereo vision system. While a monocular vision system needs properties such as geometric shape of a target, a stereo vision system enables the robot to find the position of a target without additional information. Many algorithms have been studied and developed for an object recognition. However, most of these approaches have a disadvantage of the complexity of computations and they are inadequate for real-time visual servoing. Color information is useful for simple recognition in real-time visual servoing. This paper addresses object recognition using colors, stereo matching method to reduce its calculation time, recovery of 3D space and the visual servoing.

• 전기학회논문지
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• 제60권8호
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• pp.1577-1585
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• 2011

This paper proposes a posture stabilization control algorithm for a wheeled mobile robot using hybrid visual servo control method with a position based and an image based visual servoing (PBVS and IBVS). To overcome chattering phenomena which were shown in the previous researches using a simple switching function based on a threshold, the proposed hybrid visual servo control law introduces the fusion function based on a blending function. Then, the chattering problem and rapid motion of the mobile robot can be eliminated. Also, we consider the nonlinearity of the wheeled mobile robot unlike the previous visual servo control laws using linear control methods to improve the performances of the visual servo control law. The proposed posture stabilization control law using hybrid visual servoing is verified by a theoretical analysis and simulation and experimental results.

• 제어로봇시스템학회논문지
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• 제6권6호
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• pp.462-470
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• 2000

This paper proposes a visual servoing method based on QR decomposition and disturbance observer. The QR decomposition factors the image feature Jacobian into a unitary matrix and an upper triangular matrix. And it is shown that several performance indices such as measurement sensitivity of visual features, sensitivity of the control to noise and controllability can be improved for any general image feature Jacobian by QR decomposition and disturbance observer. To show the validity of the proposed approach, visual servoing with stereo vision is carried out for a Samsung FARAMAN 6-axis industrial robot manipulator.

• 대한전기학회논문지:시스템및제어부문D
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• 제49권1호
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• pp.41-47
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• 2000

A better tracking performance can be achieved, if visual sensors such as CCD cameras are used in controling a robot manipulator, than when only relative sensors such as encoders are used. However, for precise visual servoing of a robot manipulator, an expensive vision system which has fast sampling rate must be used. Moreover, even if a fast vision system is implemented for visual servoing, one cannot get a reliable performance without use of robust and stable inner joint servo-loop. In this paper, we propose a dynamic control scheme for robot manipulators with eye-in-hand camera configuration, where a dynamic learning controller is designed to improve the tracking performance of robotic system. The proposed control scheme is implemented for tasks of tracking moving objects and shown to be robust to parameter uncertainty, disturbances, low sampling rate, etc.