• Proceedings of the Korea Society of Information Technology Applications Conference
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• 2005.11a
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• pp.229-232
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• 2005

In this paper, an image-based "approach-align -grasp" visual servo control design is proposed for the problem of object grasping, which is based on the binocular stand-alone system. The basic idea consists of considering a vision system as a specific sensor dedicated a task and included in a control servo loop, and we perform automatic grasping follows the classical approach of splitting the task into preparation and execution stages. During the execution stage, once the image-based control modeling is established, the control task can be performed automatically. The proposed visual servoing control scheme ensures the convergence of the image-features to desired trajectories by using the Jacobian matrix, which is proved by the Lyapunov stability theory. And we also stress the importance of projective invariant object/gripper alignment. The alignment between two solids in 3-D projective space can be represented with view-invariant, more precisely; it can be easily mapped into an image set-point without any knowledge about the camera parameters. The main feature of this method is that the accuracy associated with the task to be performed is not affected by discrepancies between the Euclidean setups at preparation and at task execution stages. Then according to the projective alignment, the set point can be computed. The robot gripper will move to the desired position with the image-based control law. In this paper we adopt a constant Jacobian online. Such method describe herein integrate vision system, robotics and automatic control to achieve its goal, it overcomes disadvantages of discrepancies between the different Euclidean setups and proposes control law in binocular-stand vision case. The experimental simulation shows that such image-based approach is effective in performing the precise alignment between the robot end-effector and the object.

• Proceedings of the Korea Committee for Ocean Resources and Engineering Conference
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• 2003.05a
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• pp.89-93
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• 2003

The Korea Research Institute of Ships and Ocean Engineering (KRISO), the ocean engineering branch of KORDI, has designed and manufactured a model of an autonomous underwater vehicle (AUV) to test underwater docking. This paper introduces the AUV model, ASUM, equipped with a visual servo control system to dock into an underwater station with a camera and motion sensors. To make a visual servoing AUV, this paper implemented the visual servo control system designed with an augmented state equation, which was composed of the optical flow model of a camera and the equation of the AUV's motion. The system design and the hardware configuration of ASUM are presented in this paper. A small long baseline acoustic positioning system was developed to monitor and record the AUV's position for the experiment in the Ocean Engineering Basin of KRISO, KORDI. ASUM recognizes the target position by processing the captured image for the lights, which are installed around the end of the cone-type entrance of the duct. Unfortunately, experiments are not yet conducted when we write this article. The authors will present the results for the docking test of the AUV in near future.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.1149-1152
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• 1996

Recently visual servo control is an important feature of an intelligent robot system. In this paper, we presents a Kalman filter approach for estimation of the linear optic flow model which is utilized in the visual servoing of a mobile robot. The proposed method is also compared with the conventional least mean square method via computer simulation.

• Journal of the Korean Society of Industry Convergence
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• v.18 no.2
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• pp.129-138
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• 2015

This study describe a new method to control posture and velocity for a wheeled mobile robot using visual feedback control method with a position based visual feedback. To slove the problem of vibration phenomena which were shown in the previous researches using a simple switching function based on a threshold, the proposed visual servo control law introduces the fusion function based on a blending function. The chattering problem and rapid motion of the mobile robot can be eliminated. And 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 control law using visual servoing is verified by a theoretical analysis and simulation and experimental results.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2003.10a
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• pp.213-218
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• 2003

The equipment of industrial robot in manufacturing and assembly lines has rapidly increased. In order to achieve high productivity and flexibility, it becomes very important to develop the visual feedback control system with Off-Line Programming System(OLPS). We can save much efforts and time in adjusting robots to newly defined workcells by using OLPS. A proposed visual calibration scheme is based on position-based visual feedback. The calibration program firstly generates predicted images of objects in an assumed end-effector position. The process to generate predicted images consists of projection to screen-coordinates, visible range test and construction of simple silhouette figures. Then camera images acquired are compared with predicted ones for updating position and orientation data. Computation of error is very simple because the scheme is based on perspective projection which can be also expanded to experimental results. Computation time can be extremely reduced because the proposed method does not require the precise calculation of tree-dimensional object data and image Jacobian.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.798-802
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• 2003

The robustness and reliability of vision algorithms is the key issue in robotic research and industrial applications. In this paper, the robust real time visual tracking in complex scene is considered. A common approach to increase robustness of a tracking system is to use different models (CAD model etc.) known a priori. Also fusion of multiple features facilitates robust detection and tracking of objects in scenes of realistic complexity. Because voting is a very simple or no model is needed for fusion, voting-based fusion of cues is applied. The approach for this algorithm is tested in a 3D Cartesian robot which tracks a toy vehicle moving along 3D rail, and the Kalman filter is used to estimate the motion parameters, namely the system state vector of moving object with unknown dynamics. Experimental results show that fusion of cues and motion estimation in a tracking system has a robust performance.

• Proceedings of the KIEE Conference
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• 2003.11b
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• pp.247-250
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• 2003

In this paper, we propose a robust controller for motion control of n-link robot manipulators using visual feedback. The desired joint velocity and acceleration is obtained by the feature-based visual systems and is used in the joint velocity control loop for trajectory control of the robot manipulator. We design a robust controller that compensates for bounded parametric uncertainties of robot dynamics. The stability analysis of robust joint velocity control system is shown by Lyapunov Method. The effectiveness of the proposed method is shown by simulation results on the 5-link robot manipulators with two degree of freedom.

• 제어로봇시스템학회:학술대회논문집
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• 1994.10a
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• pp.566-571
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• 1994

This paper presents in image-based visual servo control scheme for tracking a workpiece with a hand-eye coordinated robotic system using the fuzzy-neural-network. The goal is to control the relative position and orientation between the end-effector and a moving workpiece using a single camera mounted on the end-effector of robot manipulator. We developed a fuzzy-neural-network that consists of a network-model fuzzy system and supervised learning rules. Fuzzy-neural-network is applied to approximate the nonlinear mapping which transforms the features and theire change into the desired camera motion. In addition a control strategy for real-time relative motion control based on this approximation is presented. Computer simulation results are illustrated to show the effectiveness of the fuzzy-neural-network method for visual servoing of robot manipulator.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.109.5-109
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• 2002

Autonomous underwater vehicles (AUVs) are unmanned underwater vessels to investigate sea environments, oceanography and deep-sea resources autonomously. Docking systems are required to increase the capability of the AUVs to recharge the batteries and to transmit data in real time in underwater. This paper presents a visual servo control system for an AUV to dock into an underwater station with a camera. To make the visual servo control system , this paper derives an optical flow model of a camera mounted on an AUV, where a CCD camera is installed at the nose center of the AUV to monitor the docking condition. This paper combines the optical flow equation of the camera with the AUV's equation o...

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.52-55
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• 1997

This paper discusses an automatic visual-servoing system, in which a laser and a CCD camera are used for imaging the pattern of joint groove. The algorithm used here is simple and robust to find out the gap width and gap center. As a consequence, the speed of algorithm is very fast and optimized. A feature of this system is that it processes only by summing the vertical line and horizontal line of screen without any image preprocessing in order to get the energy information of lines alternatively. It is practical and useful for the system requiring a fast process time of vision.