Youngwan Cho

Analysis and design of an affine fuzzy system via bilinear matrix inequality

A novel analysis and design method for affine fuzzy systems is proposed. Both continuous-time and discrete-time cases are considered. The quadratic stability and stabilizability conditions of the affine fuzzy systems are derived and they are represented in the formulation of bilinear matrix inequalities (BMIs). Two diffeomorphic state transformations (one is linear and the other is nonlinear) are introduced to convert the plant into more tractable affine form. The conversion makes the stability and stabilizability problems of the affine fuzzy systems convex and makes the problems solvable directly by the convex linear matrix inequality (LMI) technique. The bias terms of the fuzzy controller are solved simultaneously together with the gains. Finally, the applicability of the suggested method is demonstrated via an example and computer simulation.

A study on development of home Mess-Cleanup Robot McBot

Autonomous and automatic home Mess-Cleanup Robot (Mcbot) is newly developed in this paper. So far, the vacuum-cleaner had made the burden of house chore lighten but the operational labor of a vacuum-cleaner had been so severe. Recently, the cleaning robot was commercialized to solve home cleaning labor problem but it also was not successful because it still had a problem of mess-cleanup, which was the clean-up of big trash and the arrangement of newspapers, clothes, etc. The cleaning robot just vacuum dust and so small trash but has no function to arrange the mess-up and throw away the big trash in house. For this reason, the market for the cleaning robot is not yet actively built up. So, we develop a new home mess-cleanup robot McBot to perfectly overcome this problem. It needs functions of agile navigation and novel manipulation system for mess-cleanup. The autonomous navigation system has to be controlled for the full scanning of living room and for the precise tracking of the desired path, It must be also able to recognize the absolute position and orientation of the self and to distinguish the mess object to clean-up from obstacle object to just avoid. The manipulator, which is not needed in the vacuum-cleaning robot, has the functions to distinguish big trash to clean from mess objects to arrange, to use its discretion in according to the form of mess objects and to properly carry them to the destination. We use the RFID system to sense them in this paper and propose the new disposition algorithm to have RFID tags installed on the floor and objects indoor. Then, it should be an intelligent system so that the messed-cleanup task can be autonomously performed in a wide variety of situations and environments. It needs to also have an intelligent interaction function for the human-friendly communication. Finally, the good performance of the developed McBot is confirmed through the results of the mess-cleanup experiments.

A Lyapunov Function Based Direct Model Reference Adaptive Fuzzy Control

In this paper, a direct Model Reference Adaptive Fuzzy Control (MRAFC) scheme is developed for the plant model whose structure is represented with the fuzzy state space model. The MRAFC scheme is proposed to provide asymptotic tracking of a reference signal for the systems with uncertain or slowly time-varying parameters. The developed control law and adaptive law guarantee that all signals in the closed-loop system are bounded. In addition, the plant state tracks the state of the reference model asymptotically with time for any bounded reference input signal.

Genetic Programming based Illumination Robust and Non-parametric Multi-colors Detection Model

This paper introduces GP(Genetic Programming) based color detection model for an object detection and tracking. Existing color detection methods have used linear/nonlinear transformatin of RGB color-model and improved color model for illumination variation by optimization or learning techniques. However, most of cases have difficulties to classify various of colors because of interference of among color channels and are not robust for illumination variation. To solve these problems, we propose illumination robust and non-parametric multi-colors detection model using evolution of GP. The proposed method is compared to the existing color-models for various colors and images with different lighting conditions.

Automatic Gait Generation for Quadruped Robot Using GA with an Enhancement of Performance

This Paper introduces new approach to develop fast and reliable gaits for quadruped robot using GA(genetic algorithm). Planning gaits for legged robots is a challenging task that requires optimizing parameters in a highly irregular and multidimensional space. Recent approaches have problems to select proper parameters which are not known in advance and optimize more than ten to twenty parameters simultaneously. In our approach, the effects of major gait parameters are analysed and used to guide the search more efficiently. The experiments of Sony AIBO ERS-7 in Webots environment indicate that our approach is able to produce much improved results in fast velocity and reliability.

Robust Tracking Algorithm for Moving Object using Kalman Filter and Variable Search Window Technique

This paper introduces robust tracking algorithm for fast and erratic moving object. CAMSHIFT algorithm has less computation and efficient performance for object tracking. However, the method fails to track a object if it moves out of search window by fast velocity and/or large movement. The size of the search window in CAMSHIFT algorithm should be selected manually also. To solve these problems, we propose an efficient prediction technique for fast movement of object using Kalman Filter with automatic initial setting and variable configuration technique for search window. The proposed method is compared to the traditional CAMSHIFT algorithm for searching and tracking performance of objects on test image frames.

A Trajectory Tracking Control of Wheeled Mobile Robot Using a Model Reference Adaptive Fuzzy Controller

This paper presents a design scheme of torque control for wheeled mobile robot(WMR) to asymptotically track the target reference trajectory. By considering the kinematic model of WMR, trajectory tracking control generates the desired tracking trajectory, which is transformed into the command velocity vector for the real WMR to track the target reference trajectory. The dynamic equation of the state error between the target reference trajectory and the desired tracking trajectory is represented by Takagi-Sugeno fuzzy model, and this model is used as the reference model for the real mobile robot error dynamics to follow. The control parameters are updated by adaptive laws that are designed for the error states of the real WMR to asymptotically follow the states of reference error model for the desired tracking trajectory. The proposed control is applied to a typical wheeled mobile robot and simulation studies are carried out to verify the validity and effectiveness of the control scheme.

Intelligent Modeling of User Behavior based on FCM Quantization for Smart home

In the vision of ubiquitous computing environment, smart objects would communicate each other and provide many kinds of information about user and their surroundings in the home. This information enables smart objects to recognize context and to provide active and convenient services to the customers. However in most cases, context-aware services are available only with expert systems. In this paper, we present generalized activity recognition application in the smart home based on a naive Bayesian network(BN) and fuzzy clustering. We quantize continuous sensor data with fuzzy c-means clustering to simplify and reduce BN`s conditional probability table size. And we apply mutual information to learn the BN structure efficiently. We show that this system can recognize user activities about 80% accuracy in the web based virtual smart home.

Improvement of Falling Motions for Humanoid Robot Using Injection-migration PGA

This paper introduced an automatic generation method of falling motions for humanoid robots to minimize a damage. The proposed approach used a PGA based optimization technique to find a set of joint trajectories which minimize a damage of the falling over and down. Injection-migration PGA technique is introduced and compared with EMO and various migration topologies. To verify the proposed method, experiments for falling motions were executed for Sony QRIO robot in Webots simulation environments.

Generation of Falling Motion for Humanoid Robot Using GA

This paper introduced an automatic generation method of falling motions for humanoid robots to minimize a damage. The proposed approach used a GA based optimization technique to find a set of joint trajectories which minimize a damage of the falling over and down. A couple of fitness functions are provided to generate various falling motions. To verify the proposed method, experiments for falling motions were executed for Sony QRIO robot in Webots simulation environments.