• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1603-1608
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• 2003

Multiple robotics systems with several sub-chains have a characteristic that grasp a common object with internal loading not to loose the grip. The investigation for the internal loading of a triple manipulator has been few as compared to a dual manipulator. In this paper, type of the internal loading for a triple manipulator system is investigated through analysis of the null space of the system. Several types of the internal loading are shown for general planar and spatial type triple robots, which rigidly grasp the common object. The general scheme is applied to analysis of the internal loading for the three-fingered and three-legged robots having a point contact with the grasped object.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.38 no.4
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• pp.352-362
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• 2010

The simultaneous operation of multiple UAV's makes it possible to enhance the mission accomplishment efficiency. In order to achieve this, easily scalable control algorithms are required, and swarm intelligence having such characteristics as flexibility, robustness, decentralized control, and self-organization based on behavioral model comes into the spotlight as a practical substitute. Recently, evolutionary robotics is applied to the control of UAV's to overcome the weakness of difficulties in the logical design of behavioral rules. In this paper, a neural network controller evolved by evolutionary robotics is applied to the control of multiple UAV's which have the mission of searching limited area. Several numerical demonstrations show the proposed algorithm has superior results to those of behavior based neural network controller which is designed by intuition.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.8
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• pp.738-744
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• 2013

According to the cognitive science research, the interaction intent of humans can be estimated through an analysis of the representing behaviors. This paper proposes a novel methodology for reliable intention analysis of humans by applying this approach. To identify the intention, 8 behavioral features are extracted from the 4 characteristics in human-human interaction and we outline a set of core components for nonverbal behavior of humans. These nonverbal behaviors are associated with various recognition modules including multimodal sensors which have each modality with localizing sound source of the speaker in the audition part, recognizing frontal face and facial expression in the vision part, and estimating human trajectories, body pose and leaning, and hand gesture in the spatial part. As a post-processing step, temporal confidential reasoning is utilized to improve the recognition performance and integrated human model is utilized to quantitatively classify the intention from multi-dimensional cues by applying the weight factor. Thus, interactive robots can make informed engagement decision to effectively interact with multiple persons. Experimental results show that the proposed scheme works successfully between human users and a robot in human-robot interaction.

• Journal of Institute of Control, Robotics and Systems
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• v.8 no.7
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• pp.564-572
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• 2002

This article describes the ultrasonic range sensor for the recognition of the Indoor environment, especially utilizing the multiple reflection properties of the sonar usually ignored as disturbances or noises. In this paper, we endow the ultrasonic range sensor with the active motion using the stepping servomechanism in order to get the multiple reflections with environment objects. Environment features such as target type, distance and azimuth based on the scanned one frame data of that multiple reflection patterns are recognized simultaneously.

• The Journal of Korea Robotics Society
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• v.2 no.1
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• pp.93-102
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• 2007

It is essential to estimating positions of multiple robots in order to perform cooperative task in common workspace. Accordingly, we propose a new approach of cooperative localization for multiple robots utilizing correlation among GPS errors in common workspace. Assuming that GPS data of individual robot are correlated strongly as the distance among robots are close, it is confirmed that the proposed method provides improved localization accuracy. In addition, we define two operational parameters to apply proposed method in multiple robot system. With mentioned two parameters, we present a practical solution to accumulated position error in traveling long distance.

• Journal of Institute of Control, Robotics and Systems
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• v.10 no.9
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• pp.779-784
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• 2004

This paper describes a sonic polygonal multiple reflection range sensor (SPMRS), which uses multiple reflection properties usually ignored in ultrasonic sensors as disturbances or noises. Targets such as a plane, corner, edge, or cylinder in indoor environments can easily be detected by the multiple reflection patterns obtained with a SPMRS system. Target classification and feature data extraction, such as distance and azimuth to the target, are computed simultaneously by considering the geometrical relationships between the detected targets, and finally the environment model is generated by refining the detected targets. In addition, the narrow field of view of a sonar range sensor is increased and the scanning time is reduced by active motion of the SPMRS stepping servomechanism.

• Journal of Institute of Control, Robotics and Systems
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• v.12 no.5
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• pp.497-504
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• 2006

This paper presents a new technique that derives the dynamic acceleration bounds of multiple cooperating robot systems from given individual torque limits of robots. A set of linear algebraic homogeneous equation is derived from the dynamic equations of multiple robots with friction contacts. The mobility of the robot system is analyzed by the decomposition of the null space of the linear algebraic equation. The acceleration bounds of multiple robot systems are obtained from the joint torque constraints of robots by the medium of the decomposed null space. As the joint constraints of the robots are given in the infinite norm sense, the resultant acceleration bounds of the systems are described as polytopes. Several case studies are presented to validate the proposed method in this paper.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.3
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• pp.273-283
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• 2008

This article describes a cooperative localization technique of multiple robots sharing position information of each robot. In case of conventional methods such as EKF, they need to linearization process. Consequently, they are not able to guarantee that their result is range containing true value. In this paper, we propose a method to merge the data of redundant sensors based on constraints propagation techniques on intervals. The proposed method has a merit guaranteeing true value. Especially, we apply the constraints propagation technique fusing wheel encoders, a gyro, and an inexpensive GPS receiver. In addition, we utilize the correlation between GPS data in common workspace to improve localization performance for multiple robots. Simulation results show that proposed method improve considerably localization performance of multiple robots.

• Journal of Institute of Control, Robotics and Systems
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• v.3 no.3
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• pp.244-251
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• 1997

In this paper, we propose a fault diagnosis algorithm to detect and isolate multiple faults in a system. The proposed fault diagnosis algorithm is based on a multiple fault classifier which consists of two ART2 NN(adaptive resonance theory2 neural network) modules and the algorithm is composed of three main parts - parameter estimation, fault detection and isolation. When a change in the system occurs, estimated parameters go through a transition zone in which residuals between the system output and the estimated output cross the threshold, and in this zone, estimated parameters are transferred to the multiple faults classifier for fault isolation. From the computer simulation results, it is verified that when the proposed diagnosis algorithm is performed successfully, it detects and isolates faults in the position control system of a DC motor.

• The Journal of Korea Robotics Society
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• v.8 no.2
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• pp.129-135
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• 2013

In this paper, a high precision outdoor positioning system is newly proposed using multiple GPS receivers based on the Extended Kalman Filter (EKF). Typically, the GPS signal has the instantaneous errors that degrade the positioning seriously. Using the multiple GPS receivers instead of an expensive DGPS receiver, the positioning reliability and accuracy are improved in this research as a low cost solution. To incorporate the small displacement, an INS data have been tightly coupled to the GPS data, which has the inherit disadvantage of the cumulative error occurring over time. To achieve a stabilized and accurate positioning system, the multiple GPS receiver data are fused with the INS data through the EKF process. Through real navigation experiments of an outdoor mobile robot, the performance of the proposed system has been verified to be accurate comparable to DGPS system with a lower cost.