• Journal of Institute of Control, Robotics and Systems
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• v.18 no.8
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• pp.725-730
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• 2012

In this paper, we propose the localization algorithm for the cooperative behavior of the swarm robots based on WSN (Wireless Sensor Network). The proposed method is as follows: First, we measure positions of the L-bot (Leader robot) and F-bots (Follower robots) by using the APIT (Approximate Point In Triangle) and the RSSI (Received Signal Strength Indication). Second, we measure relative positions of the F-bots against the pre-measured position of the L-bot by using trilateration. Then, to revise a position error caused by noise of the wireless signal, we use the particle filter. Finally, we show the effectiveness and feasibility of the proposed method though some simulations.

• Journal of Institute of Control, Robotics and Systems
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• v.15 no.5
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• pp.480-487
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• 2009

Autonomous Lane detection with vision is a difficult problem because of various road conditions, such as shadowy road surface, various light conditions, and the signs on the road. In this paper we propose a robust lane detection algorithm to overcome shadowy road problem using a statistical method. The algorithm is applied to the vision-based mobile robot system and the robot followed the lane with the lane following controller. In parallel with the lane following controller, the global position of the robot is estimated by the developed localization method to specify the locations where the lane is discontinued. The results of experiments, done in the region where the GPS measurement is unreliable, show good performance to detect and to follow the lane in complex conditions with shades, water marks, and so on.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.5
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• pp.428-432
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• 2010

In this paper, an adaptive formation control based on the leader-following approach is proposed for multiple mobile robots with time varying parameters. The proposed controller does not require the velocity information of the leader robot, which is commonly assumed that it is either measured or telecommunicated. In order to estimate time varying velocities of the leader robot, the smooth projection algorithm is employed. From the Lyapunov stability theory, it is proved that the proposed control scheme can guarantee the uniform ultimate boundedness of error signals of the closed-loop system. Finally, the computer simulations are performed to demonstrate the performance of the proposed control system.

• Journal of Institute of Control, Robotics and Systems
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• v.15 no.9
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• pp.959-966
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• 2009

An essential consideration when analyzing the gait of walking robots is their ability to maintain stability during walking. Therefore, this study proposes a vertical waist-jointed walking robot and gait algorithm to increase the gait stability margin while walking on the slope. First, the energy stability margin is compared according to the posture of the walking motion on slope. Next, a vertical waist-jointed walking robot is modeled to analyze the stability margin in given assumption. We describe new parameters, joint angle and position of a vertical waist-joint to get COG (center of gravity of a body) in walking. Finally, we prove the superiority of the proposed gait algorithm using simulation and conclude the results.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.2
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• pp.120-125
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• 2010

This paper proposes an intelligent PID/Fuzzy control system for two humanoid robots to transport objects stably. When a robot transports an object while walking, a whole body system of a robot may not be stable due to vibration or external factors from a different departure speed error and a body movement of walking robots. Therefore, it is necessary to measure the horizontal and vertical locations and speeds of object, then calibrate the difference of departure speed between robots with PID/Fuzzy control. The results of simulation with two robots indicated that a proposed controller makes robots to transport an object stably.

• Journal of Institute of Control, Robotics and Systems
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• v.15 no.2
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• pp.192-197
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• 2009

In this paper, we proposed the obstacle avoidance system using a single camera image and LM(Levenberg-Marquart) neural network fuzzy controller. According to a robot technology adapt to various fields of industry and public, the robot has to move using self-navigation and obstacle avoidance algorithms. When the robot moves to target point, obstacle avoidance is must-have technology. So in this paper, we present the algorithm that avoidance method based on fuzzy controller by sensing data and image information from a camera and using the LM neural network to minimize the moving error. And then to verify the system performance of the simulation test.

• Journal of Institute of Control, Robotics and Systems
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• v.15 no.2
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• pp.203-210
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• 2009

The problem of outdoor localization can be practically solved by GPS. However, GPS is not perfect and some areas of outdoor navigation should consider other solutions. This research deals with outdoor localization using an elevation map without GPS. This paper proposes a novel feature, elevation moment of inertia (EMOI), which represents the distribution of elevation as a function of distance from a robot in the elevation map. Each cell of an elevation map has its own EMOI, and outdoor localization can be performed by matching EMOIs obtained from the robot and the pre-given elevation map. The experiments and simulations show that the proposed EMOI can be usefully exploited for outdoor localization with an elevation map and this feature can be easily applied to other probabilistic approaches such as Markov localization method.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1993.06a
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• pp.1207-1210
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• 1993

There is an opinion of regarding a simple fuzzy logic controller as a kind of Variable Structure Controller in recent years. The opinion may provide an analytical basis which describes the robustness to uncertainty and the stability of a fuzzy logic controller. So in this paper, a fuzzy logic controller based on the Variable Structure System with is designed for a robot manipulator which is a class of complex, nonlinear system with uncertainty. Fuzzy control rules, membership shape of the I/O variables of the fuzzy logic controller are designed for guaranteeing the stability of an overall control system. From a computer simulation of dynamic control of a two link robot manipulator, the design procedure of the fuzzy logic controller is validated.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2010.05a
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• pp.975-978
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• 2010

This paper presents a Kalman filter based modeling algorithm for autonomous robots. State of the robot systems is measured by using embedded sensors and then carried to a host computer via ubiquitous sensor network (USN). We settle a linear state space motion equation for unknown system dynamics and modify a popular Kalman filter algorithm in deriving suitable parameter estimation mechanism. We conduct real-time experiment to test our proposed modeling algorithm where velocity state of the constructed robot is used as system observation.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.29.2-29
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• 2001

For the design of human-centered systems in which a human and machine such as a robot form a human-in system, human-friendly interaction/interface is essential. Human-friendly interaction is possible when the system is capable of recognizing human biosigns such as5 EMG Signal, hand gesture and facial expressions so the some humanintention and/or emotion can be inferred and is used as a proper feedback signal. In the talk, we report our experiences of applying the Soft computing techniques including Fuzzy, ANN, GA and rho rough set theory for efficiently recognizing various biosigns and for effective inference. More specifically, we first observe characteristics of various forms of biosigns and propose a new way of extracting feature set for such signals. Then we show a standardized procedure of getting an inferred intention or emotion from the signals. Finally, we present examples of application for our model of rehabilitation robot named.