• Journal of the Korean Society for Precision Engineering
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• v.19 no.1
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• pp.119-126
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• 2002

In this paper, we present a new approach based on an elitist genetic algorithm for the task of aligning the position of a robot gripper using CCD cameras. The vision-based control scheme for the task of aligning the gripper with the desired position is implemented by image information. The relationship between the camera space location and the robot joint coordinates is estimated using a camera-space parameter modal that generalizes known manipulator kinematics to accommodate unknown relative camera position and orientation. To find the joint angles of a robot manipulator for reaching the target position in the image space, we apply an elitist genetic algorithm instead of a nonlinear least square error method. Since GA employs parallel search, it has good performance in solving optimization problems. In order to improve convergence speed, the real coding method and geometry constraint conditions are used. Experiments are carried out to exhibit the effectiveness of vision-based control using an elitist genetic algorithm with a real coding method.

• Journal of the Korea Computer Graphics Society
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• v.24 no.3
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• pp.33-41
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• 2018

We present a secondary camera optimization method that helps the user exploring 3D virtual environment to precisely observe possible collisions between objects. The first role of our secondary camera is to automatically detect the area with the greatest possible collision. The second role is to show the detected area from a new angle of view that the current main camera cannot show. However, as the shapes of target objects are complex, the shape of the empty space between objects is also complex and narrow. It means that the space for the secondary camera position is highly constrained and its optimization can be very difficult. To avoid this difficulty and increase the efficiency of the optimization, we first compute a bisector surface between two target objects. Then, we limit the domain of the secondary camera's position on the bisector surface in the optimization process. To verify the utility of our method, we built a demonstration program in which the user can explore in a 3D virtual world and interact with objects by using a hand motion recognition device and conducted a user study.

• Journal of Institute of Control, Robotics and Systems
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• v.12 no.9
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• pp.856-860
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• 2006

A CCD camera is used to determine the position of the point sources that influence the measurement accuracy in the absolute interferometer. The principle of determination method is based on the GPS in which the position is determined by more than 3 distance information from the known positions. Two-dimensional array of photo-detectors in the CCD camera is used as known positions. Performing optimization of the cost function constructed with phase values measured at each pixel on the CCD camera, the position coordinates of each source is precisely determined.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2011.05a
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• pp.313-315
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• 2011

Smart phone camera module are mounted on the focus are 2 types depending on the behavior. AF (Auto focus) camera module and the FF (Fixed focus) camera module two are different types. AF camera module to move the location of the lens and is a way to automatically focus, FF camera module lens position of the focus is the way to a fixed state. EDOF camera module the location of the lens as a frozen state EDOF AF module using the algorithm to focus on applied technology is a module. In this paper, optimization EDOF camera module implementation of the resolution.

• The Journal of Korea Robotics Society
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• v.2 no.4
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• pp.327-333
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• 2007

We propose a navigation algorithm using image-based visual servoing utilizing a fixed camera. We define the mobile robot navigation problem as an unconstrained optimization problem to minimize the image error between the goal position and the position of a mobile robot. The residual function which is the image error between the position of a mobile robot and the goal position is generally large for this navigation problem. So, this navigation problem can be considered as the nonlinear least squares problem for the large residual case. For large residual, we propose a method to find the second-order term using the secant approximation method. The performance was evaluated using the simulation.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.12
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• pp.2498-2504
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• 2009

The fundamental research for the mobile robot navigation using the numerical optimization method is presented. We propose an image-based visual servo navigation algorithm for a wheeled mobile robot utilizing a ceiling mounted camera. For the image-based visual servoing, we define the composite image Jacobian which represents the relationship between the speed of wheels of a mobile robot and the robot's overall speed in the image plane. The rotational speed of wheels of a mobile robot can be directly related to the overall speed of a mobile robot in the image plane using the composite image Jacobian. We define the mobile robot navigation problem as an unconstrained optimization problem to minimize the cost function with the image error between the goal position and the position of a mobile robot. In order to avoid the obstacle, the modified cost function is proposed which is composed of the image error between the position of a mobile robot and the goal position and the distance between the position of a mobile robot and the position of the obstacle. The performance was evaluated using the simulation.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.5
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• pp.467-473
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• 2007

In this paper, we present a position-based robot hand tracking scheme where a pan-tilt camera is controlled such that a robot hand is always shown in the center of an image frame. We calculate the rotation angles of a pan-tilt camera by transforming the coordinate systems. In order to identify the model parameters, we applied two optimization techniques: a nonlinear least square optimizer and a particle swarm optimizer. From the simulation results, it is shown that the considered parameter identification problem is characterized by a highly multimodal landscape; thus, a global optimization technique such as a particle swarm optimization could be a promising tool to identify the model parameters of a robot hand tracking system, whereas the nonlinear least square optimizer often failed to find an optimal solution even when the initial candidate solutions were selected close to the true optimum.

• Journal of Institute of Control, Robotics and Systems
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• v.7 no.12
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• pp.1001-1008
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• 2001

This paper presents a new camera calibration algorithm for ill-conditioned cases in which the camera plane is nearly parallel to a set of non-coplanar calibration boards. for the ill-conditioned case, most of existing calibration approaches such as Tsais radial-alignment-constraint method cannot be applied. Recently, for the ill-conditioned coplanar calibration Lee&Lee[16] proposed an iterative algorithm based on the least square method. The non-coplanar calibration algorithm presented in this paper is an iterative two-stage procedure with extends the previous coplanar calibration algorithm. Through the first stage, camera, position and orientation parameters as well as one radial distortion factor are determined optimally for a given data of the scale factor and the focal length. In the second stage, the scale factor and the focal length are locally optimized. This process is repeated until any improvement cannot be expected any more Computational results are provided to show the performance of the algorithm developed.

• The Journal of Korea Robotics Society
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• v.5 no.2
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• pp.143-151
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• 2010

Automation and robotization has been required in construction for several decades and construction industry has become one of the important research areas in the field of service robotics. Especially in the steel construction, automatic recognition of structural steel members in the stockyard is emphasized. However, since the pose of steel frame in the stockyard is site dependent and also the stockyard is usually in the outdoor environment, it is difficult to determine the pose automatically. This paper adopts the recognition method based on the augmented reality to cope with this problem. Particularly focusing on the light condition of the outdoor environment, we formulated the optimization problem with the constraint and suggested the methodology to evaluate the optimal camera arrangement. From simulation results, sub-optimal solution for the position of the camera can be obtained.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2000.11a
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• pp.683-686
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• 2000

A new approach to the task of aligning a robot using camera is presented in this paper. We apply an elitist GA to find the joints angles of manipulator to reach target position instead of using nonlinear least error method. Since it employs parallel search and have good performance in solving optimization problems. In order to improve convergence speed, the floating coding method and geometry constraint conditions are used. Experiments are carried out to exhibit the effectiveness of vision-based control using elitist genetic algorithm.