• Journal of Institute of Control, Robotics and Systems
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• v.17 no.2
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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.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1994.04a
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• pp.42-48
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• 1994

This paper presents the navigation method for a mobile robot which uses a single camera and fluorescent lamp as a guide mark, projected on a convex mirror. The current position and heading direction of the mobile robot are obtained from the image of the guide mark. While the mobile robot travels to a goal position, the current position and heading direction of the mobile robot are updated continuously and the desired path and actual moving path are displayed on the monitor screen in real time. This proposed method eliminates the need to rotate the camera to track the guide mark, since a panoramic view of the surrounding area is available from the convex mirror, and natural guide marks such as usual florescent lamp on the ceiling or door frame can be used for navigation.

• Journal of Digital Contents Society
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• v.19 no.1
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• pp.35-41
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• 2018

The Q-learning algorithm based on reinforcement learning is useful for learning the goal for one behavior at a time, using a combination of discrete states and actions. In order to learn multiple actions, applying a behavior-based architecture and using an appropriate behavior adjustment method can make a robot perform fast and reliable actions. Q-learning is a popular reinforcement learning method, and is used much for robot learning for its characteristics which are simple, convergent and little affected by the training environment (off-policy). In this paper, Q-learning algorithm is applied to a lamp robot to learn multiple behaviors (human recognition, desk object recognition). As the learning rate of Q-learning may affect the performance of the robot at the learning stage of multiple behaviors, we present the optimal multiple behaviors learning model by changing learning rate.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1259-1263
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• 2004

This paper describes position estimation algorithm using neural network for the navigation of the vision-based wheeled mobile robot (WMR) in a corridor with taking ceiling lamps as landmark. From images of a corridor the lamp's line on the ceiling in corridor has a specific slope to the lateral position of the WMR. The vanishing point produced by the lamp's line also has a specific position to the orientation of WMR. The ceiling lamps have a limited size and shape like a circle in image. Simple image processing algorithms are used to extract lamps from the corridor image. Then the lamp's line and vanishing point's position are defined and calculated at known position of WMR in a corridor. To estimate the lateral position and orientation of WMR from an image, the relationship between the position of WMR and the features of ceiling lamps have to be defined. But it is hard because of nonlinearity. Therefore, data set between position of WMR and features of lamps are configured. Neural network are composed and learned with data set. Back propagation algorithm(BPN) is used for learning. And it is applied in navigation of WMR in a corridor.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.55 no.4
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• pp.161-164
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• 2006

In this thesis we designed the vision system to inspect the defect of a back light unit of plat panel display device. The vision system is divided into hardware and inspection algorithm of defect. Hardware components consist of illumination part, robot-arm controller part and image-acquisition part. Illumination part is made of acrylic panel for light diffusion and five 36W FPL's(Fluorescent Parallel Lamp) and electronic ballast with low frequency harmonics. The CCD(Charge-Coupled Device) camera of image-acquisition part is able to acquire the bright image by the light coming from lamp. The image-acquisition part is composed of CCD camera and frame grabber. The robot-arm controller part has a role to let the CCD camera move to the desired position. To take inspections of surface images of a flat panel display it can be controlled and located every nook and comer. Images obtained by robot-arm and image-acquisition board are saved on the hard-disk through windows programming and are tested whether there are defects by using the image processing algorithms.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.5
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• pp.577-582
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• 2004

This paper describes position estimation algorithm using neural network for the navigation of the vision-based Wheeled Mobile Robot (WMR) in a corridor with taking ceiling lamps as landmark. From images of a corridor the lamp's line on the ceiling in corridor has a specific slope to the lateral position of the WMR. The vanishing point produced by the lamp's line also has a specific position to the orientation of WMR. The ceiling lamps has a limited size and shape like a circle in image. Simple image processing algorithms are used to extract lamps from the corridor image. Then the lamp's line and vanishing point's position are defined and calculated at known position of WMR in a corridor To estimate the lateral position and orientation of WMR from an image, the relationship between the position of WMR and the features of ceiling lamps have to be defined. Data set between position of WMR and features of lamps are configured. Neural network are composed and teamed with data set. Back propagation algorithm(BPN) is used for learning. And it is applied in navigation of WMR in a corridor.

• Journal of the Korean Society for Precision Engineering
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• v.23 no.3 s.180
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• pp.132-138
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• 2006

With a great requirement of innovation caused by severe competition current companies are encouraged to improve bottleneck areas in production procedure. Specially a chassis line in which assembly processes are mainly carried out manually has the large potential to be automated. The putting of spare tire in trunk in chassis line is still dominated by free dropping method. Through that, parts in trunk such as luggage room lamp, jack and so on were damaged and the complaint of assembler in the next process was occurred due to physical strength. To eliminate these, tile robot system was in this paper developed to place spare tire on the mounting hole in trunk. The movement of robot was synchronized with the velocity of chassis hanger. With this automated system the productivity of the chassis line was increased from the benefits such as simplification of the system using only robot without the mechanically synchronized transport, inserting spare tire into the right position with robot, reduction of damaged parts and production of various type of car.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.41.1-41
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• 2002

This paper describes a robust landmark matching method to reduce ambiguity of candidate of landmark. General robot system acquires the candidate of landmark through vision sensor in outdoor environment. Our robot uses the omnidirectional vision system to get all around the view. Thus, the robot obtains more candidates of landmark than the conventional vision system. To obtain the candidates of landmark, robot uses the two types of feature. They are vertical edge and merged region of vertical edges. The former is to extract the vertical line of building, street lamp, etc. The latter is to reduce ambiguity of vertical edge in similar region. It is difficult to match the candidates of landmark...

• Proceedings of the KIEE Conference
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• 2002.11c
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• pp.154-158
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• 2002

This paper describes a path tracking method for vision-based and autonomous mobile robot in a corridor. At first, we extract the ceiling-lamp of the corridor through simple preprocessing (gray, thresholding, labeling, etc.) for robot position and orientation. Then, we design the controller for path-tracking. Simulations conducted, and acceptable vehicle localization results were obtained to prove the feasibility of the proposed approach.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1163-1168
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• 2005

This paper proposes a soft-remote-control (soft-remocon) system based on EMG signals for the Intelligent Sweet Home. The proposed system is applied to Intelligent Sweet Home which was developed to help the independence living of the elderly and physically handicapped individuals. The goal of proposed system is to control home-installed electronic devices such as TV, air-conditioner, curtain and lamp in Intelligent Sweet Home using EMG signals. Features such as VAR and DAMV having good separability performance are selected for pattern classification. FMMNN is adopted as a pattern classifier. Classification results are allowed to a developed remote control module and then corresponding infrared pulses can operate home-installed electronic devices. We concluded that EMG as an input interface for home-installed electronic devices in Intelligent Sweet Home.