• Proceedings of the Korea Society of Information Technology Applications Conference
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• 2005.11a
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• pp.113-117
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• 2005

This paper describes a visual control scheme, fuzzy logic system for visual servoing of an autonomous mobile robot. An existing communication autonomous mobile robot always needs to keep the object in image to detect the moving object. This is a problem in an autonomous mobile robot for spontaneous activity. To solve it, some features for an object are taken from an image and then use in the design of fuzzy logic system for decision of moving location and direction of visual servoing contrivance(apparatus). So continuous tracking is possible by moving the visual servoing contrivance. We present some simulation results and further studies in the Section of Simulation and Concluding Remarks.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.767-771
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• 2003

In this study, stereo vision system is applied to a mobile manipulator for effective tasks. The robot can recognize a target and compute the position 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. However, color information is useful for simple recognition in real-time visual servoing. In this paper, we refer to about object recognition using colors, stereo matching method, recovery of 3D space and the visual servoing.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.5
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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.

• Journal of the Korean Society for Precision Engineering
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• v.20 no.10
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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.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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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 the Korean Institute of Intelligent Systems
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• v.16 no.4
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• pp.454-459
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• 2006

The research and development for autonomous mobile robots has widely been reported. This paper describes a fuzzy logic based visual servoing system for an autonomous mobile robot. An existing system always needs to keep a moving object in overall image. This makes difficult to move the autonomous mobile robot spontaneously. In this paper we first explain an autonomous mobile robot and fuzzy logic system. And then we design a fuzzy logic based visual servoing system. We extract some features of the object from an overall image and then design a fuzzy logic system for controlling the visual servoing system to an exact position. We here introduce a shooting robot that can track an object and hit it. We show that the proposed system presents a desirable performance by a computer simulation and some experiments.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.8
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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.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.49 no.1
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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.

• The Journal of Korea Robotics Society
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• v.1 no.2
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• pp.125-134
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• 2006

The problem of establishing the servo system to reach the desired location keeping all features in the field of view and following a straight line is considered. In addition, robustness of camera calibration parameters is considered in this paper. The proposed approach is based on switching from position-based visual servoing (PBVS) to image-based visual servoing (IBVS) and allows the camera path to follow a straight line. To achieve the objective, a pose estimation method is required; the camera's target pose is estimated from the obtained images without the knowledge of the object. A switched control law moves the camera equipped to a robot end-effector near the desired location following a straight line in Cartesian space and then positions it to the desired pose with robustness to camera calibration error. Finally simulation results show the feasibility of the proposed visual servoing technique.

• Journal of the Korean Society for Precision Engineering
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• v.21 no.11
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• pp.83-90
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• 2004

In this paper we present a new real-time visual servoing unit for laparoscopic surgery This unit can automatically control laparoscope manipulator through visual tracking of laparoscopic surgical tool. For the tracking, we present two-stage adaptive CONDENSATION(conditional density propagation) algorithm to extract the accurate position of the surgical tool tip from a surgical image sequence in real-time. This algorithm can be adaptable to abrupt change of laparoscope illumination. For the control, we present virtual damper system to control a laparoscope manipulator safely and stably. This system causes the laparoscope to move under constraint of the virtual dampers which are linked to the four sides of image. The visual servoing unit operates the manipulator in real-time with locating the surgical tool in the center of image. The experimental results show that the proposed visual tracking algorithm is highly robust and the controlled manipulator can present stable view with safe.