• 제어로봇시스템학회:학술대회논문집
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• 1991.10a
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• pp.935-938
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• 1991

We are developing an automatic adjusting system for ITC. ITC(Integrated Tube Components) has a large set-by-set variability in its characteristics. And it also has nonlinearities. It requires not only a fast vision process but also an efficient control algorithm to meet the need for high productivity. In this paper, the description of an adjusting system and the modelling of ITC will be presented. And also the concept of a new rule based hierarchical algorithmic approaches will be suggested.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.1509-1512
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• 1996

This paper presents an intelligent autopilot for STT missiles with multiple controllers. The mixed H$_{2}$/H$_{\infty}$ control technique is applied for each controller and implemented by using the genetic searching algorithm. To facilitate automatic switching of multiple controllers under different operating conditions, an error based switching scheme is also combined with the multiple controllers at the higher level, which constitutes a hierarchical intelligent control system. It is shown via computer simulation that the proposed autopilot outperforms the conventional one..

• Journal of Power System Engineering
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• v.21 no.4
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• pp.26-33
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• 2017

In this paper, we developed a control algorithm to maximize the cleaning performance and the cleaning efficiency of the underwater cleaning robot platform which has been developed for various cistern environment in the industrial field. Through these research and development, we have presented the operation and application of underwater cleaning robots that have been developed, and contributed to commercialization. Finally, this results were verified the effectiveness through actual field experiments.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.5
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• pp.598-603
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• 2007

To solve the rule explosion problem in multi-input fuzzy system, a method of converting a given fuzzy system to 2 layered hierarchical fuzzy system has been reported, where at the 1st layer, linearly independent fuzzy rule vectors generated from the given fuzzy system are used and, at the 2nd layer, linear combinations of these independent fuzzy rule vectors are used. In this paper, the steapest descent algorithm is presented to learn the fuzzy rule vectors and related coefficients for the equivalent 2 layered hierarchical structure. By simulation of learning of ball and beam control system, the feasibility of proposed learning scheme is shown.

• Journal of Institute of Control, Robotics and Systems
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• v.4 no.4
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• pp.458-463
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• 1998

This paper presents an autopilot design method for STT missiles using the intelligent control technique and multiple controllers. The mixed $H_2/H_{\infty}$ control technique is applied for each controller design and the control gains are implemented by using the genetic searching algorithm. To facilitate automatic switching of multiple controllers under different operating conditions, an error based switching scheme is also combined with the multiple controllers at a higher level, which constitutes a hierarchical intelligent control system. It is shown via computer simulation that the proposed autopilot outperforms the conventional one.

• Journal of IKEEE
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• v.11 no.4
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• pp.307-314
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• 2007

In this paper, we propose an image contrast enhancement algorithm for an LCD TV. The proposed algorithm consists of two processes: the image segmentation process and the tone curve control process. The first process uses an automatic threshold technique to decompose an input image into two regions and then utilizes a hierarchical structure for real-time processing. The second process generates a gray level tone curve for contrast enhancement using a weighted sum of average tone curves for two segmented regions. Experimental result shows that the proposed algorithm outperforms the conventional contrast enhancement methods for an LCD TV.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.8
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• pp.810-816
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• 2007

A security robot system named EGIS-SR is a mobile security robot through one of the new growth engine project in robotic industries. It allows home surveillance through an autonomous mobile platform using onboard cameras and wireless security sensors. EGIS-SR has many sensors to allow autonomous navigation, hierarchical control architecture to handle lots of situations in monitoring home surveillance and mighty networks to achieve unmanned security services. EGIS-SR is tightly coupled with a networked security environment, where the information of the robot is remotely connected with the remote cockpit and patrol man. It achieved an intelligent unmanned security service. The robot is a two-wheeled mobile robot and has casters and suspension to overcome a doorsill. The dynamic motion is verified through $ADAMS^{TM}$ simulation. For the main controller, PXA270 based hardware platform based on linux kernel 2.6 is developed. In the linux platform, data handling for various sensors and the localization algorithm are performed. Also, a local path planning algorithm for object avoidance with ultrasonic sensors and localization using $StarGazer^{TM}$ is developed. Finally, for the automatic charging, a docking algorithm with infrared ray system is implemented.

• Proceedings of the KIEE Conference
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• 2007.10a
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• pp.333-334
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• 2007

We propose a path planning method to decrease a inspection lead time of line scan camera in SMT(surface mount technology) in-line system. The inspection window area of printed circuit board should be minimized to consider the FOV(field of view) of line scan camera so that line scan inspector is going to find a optimal solution of path planning. We propose one of the hierarchical clustrering algorithm for a given board. Comparative simulation results are presented to verify the usefulness of proposed method.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.12
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• pp.3315-3337
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• 2012

Crowded scenes analysis is a challenging topic in computer vision field. How to detect diverse motion patterns in crowded scenarios from videos is the critical yet hard part of this problem. In this paper, we propose a novel approach to mining motion patterns by utilizing motion information during both long-term period and short interval simultaneously. To capture long-term motions effectively, we introduce Motion History Image (MHI) representation to access to the global perspective about the crowd motion. The combination of MHI and optical flow, which is used to get instant motion information, gives rise to discriminative spatial-temporal motion features. Benefitting from the robustness and efficiency of the novel motion representation, the following motion pattern mining is implemented in a completely unsupervised way. The motion vectors are clustered hierarchically through automatic hierarchical clustering algorithm building on the basis of graphic model. This method overcomes the instability of optical flow in dealing with time continuity in crowded scenes. The results of clustering reveal the situations of motion pattern distribution in current crowded videos. To validate the performance of the proposed approach, we conduct experimental evaluations on some challenging videos including vehicles and pedestrians. The reliable detection results demonstrate the effectiveness of our approach.