Based on the sliding mode control theory, a decentralized controller design method is developed for a large scale system with a poly topic model. In terms of LMIs, we derive sufficient conditions for the existence of the decentralized controller guaranteeing a stable sliding motion. We also give an LMI-based control design algorithm. Finally, the proposed method is applied to decentralized stabilization of double-inverted pendulums. Simulation results show that our method gives not only the robust stability but perfect rejection of norm-bounded uncertainties.

An adaptive formation control approach is proposed for nonhonolomic multiple mobile robots considering unknown slipping and skidding. It is assumed that unknown slipping and skidding effects are bounded by unknown constants. Under this assumption, the adaptive technique is employed to estimate the bounds of unknown slipping and skidding effects of each mobile robot. To deal with the skidding effect included in kinematics, the dynamic surface design approach is applied to design a local controller for each mobile robot. Using Lyapunov stability theorem, the adaptation laws for tuning bounds of slipping and skidding are induced and it is proved that all signals of the closed-loop system are bounded and the tracking errors and the synchronization errors of the path parameters converge to an adjustable neighborhood of the origin. Finally, simulation results are provided to verify the effectiveness of the proposed approach.

The oil tanker ship over 150GRT must equip oil content meter which satisfy requirements of revised MARPOL 73/78. Online measurement of oil content in complex samples is required to have fast response, continuous measurement, and satisfaction of ${\pm}10ppm$ or ${\pm}10%$ error in this field. The research of this paper is to develop oil content measurement system using analysis of light transmission and scattering among turbidity measurement methods. Light transmission and scattering are analytical methods commonly used in instrumentation for online turbidity measurement of oil in water. Gasoline is experimented as a sample and the oil content approximately ranged from 14ppm to 600ppm. TSK Fuzzy Model may be suitable to associate variously derived spectral signals with specific content of oil having various interfering factors. Proposed Parallel TSK Fuzzy Model is reasonably used to classify oil content in comparison with other models. Those measurement methods would be effectively applied and commercialized to oil content meter that is key components of oil discharge monitoring control equipment.

In this paper, we address an active ranging system based on laser structured light image for mobile robot application. Since the burdensome correspondence problem is avoidable, the structured light image processing has efficient computation in comparison with the conventional stereo image processing. By using a cylindrical lens in the laser generation, it is possible to convert a point laser into a stripe laser without motorized scan in the proposed system. In order to achieve robustness against environmental illumination noise, we propose an efficient integro-differential image processing algorithm. The proposed system has embedded image processing module and transmits distance data to reduce the computational burden in main control system.

The paper proposes a hierarchical fault detection method for the high voltage equipment using a microphone array which detects the location of fault and the thermal imaging and CCD cameras which verifies the fault and stores the image, respectively. There are partial arc discharges on the faulty insulators, which generates a specific pattern of sound. Detecting the signal using the microphone array, the location of the faulty insulator can be estimated. The 6th band-pass filter was applied to remove noise signal from wind or external influence. When the mobile robot carries the thermal and CCD cameras to the possible place of the fault insulator, the fault insulators or power transmission wires can be detected by the thermal images, which are caused by the aging or natural erosion. Finally, the CCD camera captures the image of the fault insulator for the record. The detection scheme of fault location using the microphone array and the thermal images have been proved to be effective through the real experiments. As a result of this research, it becomes possible to use a mobile robot with the integrated sensors to detect the fault insulators instead of a human being.

The interaction of emotion is an important factor in Human-Robot Interaction(HRI). This requires a contextual appraisal of emotion extracting the emotional information according to the events happened from past to present. In this paper an emotion appraisal system based on the cognitive context is presented. Firstly, a conventional emotion appraisal model is simplified to model a contextual emotion appraisal which defines the types of emotion appraisal, the target of the emotion induced from analyzing emotional verbs, and the transition of emotions in the context. We employ a language based cognitive system and its sentential memory and object descriptor to define the type and target of emotion and to evaluate the emotion varying with the process of time with the a priori emotional evaluation of targets. In a experimentation, we simulate the proposed emotion appraisal system with a scenario and show the feasibility of the system to HRI.

This paper presents a simultaneous localization and mapping (SLAM) of an indoor hallway environment using Rao-Blackwellized particle filter (RBPF) along with a line segment as a landmark. Based on the fact that fluent line features can be extracted around the ceiling and side walls of hallway using vision sensor, a horizontal line segment is extracted from an edge image using Hough transform and is also tracked continuously by an optical flow method. A successive observation of a line segment gives initial state of the line in 3D space. For data association, registered feature and observed feature are matched in image space through a degree of overlap, an orientation of line, and a distance between two lines. Experiments show that a compact environmental map can be constructed with small number of horizontal line features in real-time.

In this paper, we introduce a new path planning algorithm which combines the merits of a visibility graph algorithm and an adaptive cell decomposition. We quantize a given map with empty cells, blocked cells, and mixed cells, then find the optimal path on the quantized map using a visibility graph algorithm. For reducing the number of the quantized cells we use the quad-tree technique which is used in an adaptive cell decomposition, and for improving the performance of the visibility checking in making a visibility graph we propose a new visibility checking method which uses the property of the quad-tree instead of the well-known rotational sweep-line algorithm. For the more efficient visibility checking, we propose two additional improvements for our suggested method. Both of them are used for reducing the visited cells in the quad-tree. The experiments for a performance comparison of our algorithm with other well-known algorithms show that our proposed method is superior to others.

We propose a motion planning method for autonomous mobile robots. In order to minimize traveling time, a smooth path and a time optimal velocity profile should be generated under kinematic and dynamic constraints. In this paper, we develop an effective and practical method to generate a good solution with lower computation time. The initial path is obtained from voronoi diagram by Dijkstra's algorithm. Then the path is improved by changing the graph and path simultaneously. We apply the dynamic programming algorithm into the stage of improvement. Simulation results are presented to verify the performance of the proposed method.

This paper proposes networked swarm robotic systems with group based control scheme using spring damper impendence feature. The proposed algorithm is applied to keep system arrangement in unexpected situations based on the spring-damper impedance and fuzzy logic. Using the proposed scheme, each robot overcome collision problems efficiently. The structure of UBSR (UMPC Based Swarm Robot) system consists of user level, cognitive level, and executive level. This structure is designed to easily meet the different configuration requirements for other levels. Simulation results show an availability of the proposed method.

The segmentation of moving object in video sequence is a core technique of intelligent image processing system such as video surveillance, traffic monitoring and human tracking. A typical method to segment a moving region from the background is the background subtraction. The steps of background subtraction involve calculating a reference image, subtracting new frame from reference image and then thresholding the subtracted result. One of famous background modeling is Gaussian mixture model (GMM). Even though the method is known efficient and exact, GMM suffers from a problem that includes false pixels in ROI (region of interest), specifically shadow pixels. These false pixels cause fail of the post-processing tasks such as tracking and object recognition. This paper presents a method for removing false pixels included in ROT. First, we subdivide a ROI by using shape characteristics of detected objects. Then, a method is proposed to classify pixels from using histogram characteristic and comparing difference of energy that converts the color value of pixel into grayscale value, in order to estimate whether the pixels belong to moving object area or shadow area. The method is applied to real video sequence and the performance is verified.

An analytical method for robust design of the multi-loop proportional-integral (PI) controller is proposed for various types of multi-delay processes. On the basis of the direct synthesis and generalized IMC-PID approach, the analytical tuning rules of the multi-loop PI controller are firstly derived for achieving the desired closed-loop response, and the structured singular value synthesis is then utilized for the tradeoffs between the robust stability and performance by adjusting only one design parameter (i.e., the closed-loop time constant). To verify the superiority of the proposed method, the simulation studies have been conducted on a wide variety of multivariable processes. The multi-loop PI controller designed by the proposed method shows a fast, well-balanced and robust response with the minimum integral absolute error (IAE) in compared with other renowned methods.

If an appliance perceives the location or health condition of a resident in the smart home, it can provide more intelligent service actively. That is, while the conventional appliance is operated by manual input of a resident, the location-based human adaptive appliance detects the resident's information such as location, activity pattern, or health condition by itself and provides the most suitable living condition for the resident autonomously. This paper presents the real-time location-based metabolic rate estimation method that measures the amount of physical activity (metabolic rate) for location-based human adaptive air-conditioner. And, the feasibility of the algorithm is evaluated experimentally on a test bed using the pyroelectric infrared sensor-based indoor location aware system (PILAS) that is a non-terminal-based location-aware system.

This paper describes the development of integrated head and eye tracker system. Vision based head tracker is performed and it has 7mm error in 300mm translation. The epi-polar method and point matching are used for determining a position of head and rotational degree. High brightness LEDs are installed on helmet and the installed pattern is very important to match the points of stereo system. Eye tracker also uses LED for constant illumination. A Position of gazed object(3m distance) is determined by pupil tracking and eye tracker has 1~5 pixel error. Integration of result data of each tracking system is important. RS-232C communication is applied to integrated system and triggering signal is used for synchronization.

This paper proposes novel genetic design of optimal classifier ensemble for vehicle detection using Genetic Algorithm with Varying Population Size (GAVaPS). Recently, many classifiers are used in classifier ensemble to deal with tremendous amounts of data. However the problem has a exponential large search space due to the increasing the number of classifier pool. To solve this problem, we employ the GAVaPS which outperforms comparison with simple genetic algorithm (SGA). Experiments are performed to demonstrate the efficiency of the proposed method.