• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.8
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• pp.2529-2551
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• 2022

Visual servoing (VS) based on the Kalman filter (KF) algorithm, as in the case of KF-based image-based visual servoing (IBVS) systems, suffers from three problems in uncalibrated environments: the perturbation noises of the robot system, error of noise statistics, and slow convergence. To solve these three problems, we use an IBVS based on KF, African vultures optimization algorithm enhanced extreme learning machine (AVOA-ELM), and fuzzy logic (FL) in this paper. Firstly, KF online estimation of the Jacobian matrix. We propose an AVOA-ELM error compensation model to compensate for the sub-optimal estimation of the KF to solve the problems of disturbance noises and noise statistics error. Next, an FL controller is designed for gain adaptation. This approach addresses the problem of the slow convergence of the IBVS system with the KF. Then, we propose a visual servoing scheme combining FL and KF-AVOA-ELM (FL-KF-AVOA-ELM). Finally, we verify the algorithm on the 6-DOF robotic manipulator PUMA 560. Compared with the existing methods, our algorithm can solve the three problems mentioned above without camera parameters, robot kinematics model, and target depth information. We also compared the proposed method with other KF-based IBVS methods under different disturbance noise environments. And the proposed method achieves the best results under the three evaluation metrics.

• Journal of Institute of Control, Robotics and Systems
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• v.12 no.3
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• pp.248-254
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• 2006

It is necessary to improve the exactness and adaptation of the working environment for the intelligent robot system. The vision sensor have been studied for a long time at this points. However, it has many processes and difficulties for the real usages. This paper proposes a visual servoing in the virtual environment to support OLP(Off-Line-Programming) path compensation and supplement the problem of complexity of the old kinematical calibration. Initial robot path could be compensated by pixel differences between real and virtual image. This method removes the varies calibrations and 3D reconstruction process in real working space. To show the validity of the proposed approach, virtual space servoing with stereo camera is carried out with WTK and openGL library for a KUKA-6R manipulator and updated real robot path.

• Proceedings of the KIEE Conference
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• 2007.07a
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• pp.1771-1772
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• 2007

The purpose of this project is to develop the visual servoing system with 5d.o.f robot manipulator. For this, we developed robot manipulator by using 5 serial RC motors and the visual system is also developed by using low cost USB CCD camera. RISC MPU ATMEGA128 is main controller MPU for the robot manipulator. To control the manipulator Kinematics was analyzed and GUI, API for vision system also were developed.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.10
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• pp.1876-1882
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• 2008

Nano manipulator is used to manufacture Carbon NanoTube(CNT) tips. Using nano manipulator, operator attaches a CNT at the apex of Atomic Force Microscope(AFM) tip, which requires a mastery of mechanics and long manufacture time. Nano manipulator is installed inside a Scanning Electron Microscope(SEM) chamber to observe the operation. This paper presents a control scheme for horizontal axes of nano manipulator via processing SEM image. Edges of AFM tip and CNT are first detected, and the position information so obtained is fed to control horizontal axes of nano manipulator. That is, a visual servoing loop is realized to control the axes more precisely in nano scale.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.410-414
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• 1996

A visual servoing algorithm is proposed for a robot with a camera in hand. Specifically, novel image features are suggested by employing a viewing model of perspective projection to estimate relative pitching and yawing angles between the object and the camera. To compensate dynamic characteristics of the robot, desired feature trajectories for the learning of visually guided line-of-sight robot motion are obtained by measuring features by the camera in hand not in the entire workspace, but on a single linear path along which the robot moves under the control of a, commercially provided function of linear motion. And then, control actions of the camera are approximately found by fuzzy-neural networks to follow such desired feature trajectories. To show the validity of proposed algorithm, some experimental results are illustrated, where a four axis SCARA robot with a B/W CCD camera is used.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.302-305
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• 1996

This paper presents a visual servoing combined by Neural Network with optimal structure and predictive control for robotic manipulators to tracking or grasping of the moving object. Using the four feature image information from CCD camera attached to end-effector of RV-M2 robot manipulator having 5 dof, we want to predict the updated position of the object. The Kalman filter is used to estimate the motion parameters, namely the state vector of the moving object in successive image frames, and using the multi layer feedforward neural network that permits the connection of other layers, evolutionary programming(EP) that search the structure and weight of the neural network, and evolution strategies(ES) which training the weight of neuron, we optimized the net structure of control scheme. The validity and effectiveness of the proposed control scheme and predictive control of moving object will be verified by computer simulation.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.41.4-41
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• 2002

In this paper we deal with visual servoing that can control a robot arm with a camera using information of images only, without estimating 3D position and rotation of the robot arm. Here it is assumed that the robot arm is calibrated and the camera is uncalibrated. Here we consider two coordinate systems, the world coordinate system and the camera coordinate one and we use a pinhole camera model as the camera one. First of all, the essential notion can be show, that is, epipolar geometry, epipole, epipolar equation, and epipolar constrain. And these plays an important role in designing visual servoing in the later chapters. Statement of the problem is giver. Provided two a priori...

• Proceedings of the IEEK Conference
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• 2006.06a
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• pp.837-838
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• 2006

This paper proposes a method of assembling parts using visual servoing in dynamic environment. We use SSD(Sum of Square Difference) based on adaptive template in order to detect a moving object in the case where the robot and the object both move. And the control input of the robot is obtained from the feed-back signal of the feature movement and the feed-forward signal of the camera movement in image plane.

• Proceedings of the KIEE Conference
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• 2007.10a
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• pp.251-252
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• 2007

Nano manipulator is used to manufacture Carbon NanoTube(CNT) tips. Using nano manipulator operator attaches a CNT at the end of Atomic Force Microscopy(AFM) tip, which requires a master mechanic and long manufacture time. Nano manipulator is installed inside Scanning Electron Microscopy (SEM) chamber to observe the operation. This paper presents a control of horizontal axis of nano manipulator via processing SEM image. Edges of AFM tip and CNT are first detected, the position information so obtained is fed to control horizontal axis of nano manipulator. To be specific, visual servoing loop was realized to control the axis more precisely.

• Proceedings of the KIEE Conference
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• 1996.07b
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• pp.1269-1271
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• 1996

This paper presents a visual servoing combined by evolutionary algorithms and neural network for a robotic manipulators to control position and orientation of the end-effector. Using the multi layer feedforward neural network that permits the connection of other layers, evolutionary programming(EP) that search the structure and weight of the neural network, and evolution strategies(ES) which training the weight of neuron, we optimized the net structure of control scheme. Using the four feature image information from CCD camera attached to end-effector of RV-M2 robot manipulator having 5 dof, we generate the control input to agree the target image, to realize the visual servoing. The validity and effectiveness of the proposed control scheme will be verified by computer simulations.