• 제어로봇시스템학회논문지
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• 제17권2호
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• pp.164-170
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• 2011

This paper proposes a novel monocular vision-based SLAM (Simultaneous Localization and Mapping) method using both position and orientation information of ceiling lamps. Conventional approaches used corner or line features as landmarks in their SLAM algorithms, but these methods were often unable to achieve stable navigation due to a lack of reliable visual features on the ceiling. Since lamp features are usually placed some distances from each other in indoor environments, they can be robustly detected and used as reliable landmarks. We used both the position and orientation of a lamp feature to accurately estimate the robot pose. Its orientation is obtained by calculating the principal axis from the pixel distribution of the lamp area. Both corner and lamp features are used as landmarks in the EKF (Extended Kalman Filter) to increase the stability of the SLAM process. Experimental results show that the proposed scheme works successfully in various indoor environments.

• 제어로봇시스템학회논문지
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• 제12권9호
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• pp.843-849
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• 2006

Intelligent Space defines an environment where many intelligent devices, such as computers and sensors, are distributed. As a result of the cooperation between smart devices, intelligence emerges from the environment. In such scheme, a crucial task is to obtain the global location of every device in order to of for the useful services. Some tracking systems often prepare the models of the objects in advance. It is difficult to adopt this model-based solution as the tracking system when many kinds of objects exist. In this paper the location is achieved with no prior model, using color properties as information source. Feature vectors of multiple objects using color histogram and tracking method are described. The proposed method is applied to the intelligent environment and its performance is verified by the experiments.

• 한국정보기술응용학회:학술대회논문집
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• 한국정보기술응용학회 2005년도 6th 2005 International Conference on Computers, Communications and System
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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.

• 한국산업융합학회 논문집
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• 제22권4호
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• pp.447-457
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• 2019

The intelligent sensory system is required to ensure the accurate welding performance. This paper describes the development of an intelligent vision sensor for the robotic laser welding. The sensor system includes a PC based vision camera and a stripe-type laser diode. A set of robust image processing algorithms are implemented. The laser-stripe sensor can measure the profile of the welding object and obtain the seam line. Moreover, the working distance of the sensor can be changed and other configuration is adjusted accordingly. The robot, the seam tracking system, and CW Nd:YAG laser are used for the laser welding robot system. The simple and efficient control scheme of the whole system is also presented. The profile measurement and the seam tracking experiments were carried out to validate the operation of the system.

• International Journal of Automotive Technology
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• 제3권2호
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• pp.71-78
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• 2002

A new control method far vision-based autonomous vehicle is proposed to determine navigation direction by analyzing lane information from a camera and to navigate a vehicle. In this paper, characteristic featured data points are extracted from lane images using a lane recognition algorithm. Then the vehicle is controlled using new Levenberg-Marquardt neural network algorithm. To verify the usefulness of the algorithm, another algorithm, which utilizes the geometric relation of a camera and vehicle, is introduced. The second one involves transformation from an image coordinate to a vehicle coordinate, then steering is determined from Ackermann angle. The steering scheme using Ackermann angle is heavily depends on the correct geometric data of a vehicle and a camera. Meanwhile, the proposed neural network algorithm does not need geometric relations and it depends on the driving style of human driver. The proposed method is superior than other referenced neural network algorithms such as conjugate gradient method or gradient decent one in autonomous lateral control .

• International Journal of Control, Automation, and Systems
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• 제6권6호
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• pp.828-835
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• 2008

We present a novel method for eye location by means of a two-level classifier scheme. Locating the eye by machine-inspection of an image or video is an important problem for Computer Vision and is of particular value to applications in biomedical imaging. Our method aims to overcome the significant challenge of an eye-location that is able to maintain high accuracy by disregarding highly variable changes in the environment. A first level of computational analysis processes this image context. This is followed by object detection by means of a two-class discrimination classifier(second algorithmic level).We have tested our eye location system using FERET and BioID database. We compare the performance of two-level classifier with that of non-level classifier, and found it's better performance.

• International Journal of Control, Automation, and Systems
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• 제3권spc2호
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• pp.363-375
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• 2005

The paper describes some of the challenges that face the control of nonlinear interconnected power systems. The challenges include the selection of appropriate control and information structures that could range from a completely decentralized to a fully centralized structure. Once a structure is proven to be feasible, the effectiveness of control signals needs to be assessed. Analytical tools are derived for this purpose in the first part of the paper, and they are illustrated with a case study that involves the design of a damping decentralized controller using a Thyristor Controlled Series Compensation device. The second part of the paper deals with the load following and tracking problem through automatic generation control for a system that has been re-structured or deregulated. This problem can be solved using a completely decentralized scheme. It is solved here using fuzzy rules and with an emphasis on compliance with NERC's standards and reduction of wear and tear of the equipment. It is illustrated with a test system that has three interconnected control areas. Finally, comments on the economics of control and the author's vision are presented.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 1996년도 추계학술대회 논문집
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• pp.323-327
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• 1996

Gap and thickness difference information between blanks are often necessary for tailored blank welding quality evaluation , optimum welding parameters selection and evaluation of shearing machine, blink allocation device accuracy and clamping device. We develope 3D vision system and camera unit using structured lighting for this purpose. A simple ar d efficient scheme for gap and thickness feature recognition Is developed as well as measurements. Experimental results shows this system measuring accuracy is 10 ${\mu}{\textrm}{m}$ and 16${\mu}{\textrm}{m}$ for gap and thickness difference respectively The data are expexed to be useful for preview gap control.

• 한국레이저가공학회지
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• 제12권2호
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• pp.11-16
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• 2009

A new profile measurement sensor was developed for remote laser welding robots. A stripe laser and a vision camera are used in the profile sensor. A simple sensor guided control scheme using the developed sensor is also introduced. The sensor can be used to guide the welding head in the remote welding application, where the working distance reaches to 450mm. In experiments, the profile measurement and the seam tracking were carried out using the developed sensor.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2000년도 하계종합학술대회 논문집(4)
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• pp.163-166
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• 2000

Real-time traffic detection scheme based on Computer Vision is capable of efficient traffic control using automatically computed traffic information and obstacle detection in moving automobiles. Traffic information is extracted by segmenting vehicle region from road images, in traffic detection system. In this paper, we propose the advanced segmentation of vehicle from road images using multiple local region information. Because multiple local region overlapped in the same lane is processed sequentially from small, the traffic detection error can be corrected.