• 전자공학회논문지 IE
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• v.48 no.4
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• pp.30-39
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• 2011

This paper proposed a new concept of information space called Smart Floor. Smart Floor is an intelligent space where a mobile robot can read and write specific information through Radio Frequency IDentification (RFID) tags which are mounted on Smart Floor to drive its goal position. RFID tag packaging technology is described for building Smart Floor. Also a mobile robot equipped passive RFID System with ultra high frequency (UHF) bandwidth has developed. The information that consists of an absolute position in the Smart Floor and desired direction saved on RFID tags is a simulated Q-value based on Q-learning algorithm. Proposed Smart Floor will be a proper method to communicate between space and robot.

• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.1
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• pp.48-53
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• 2009

In this paper, we propose an efficient method of representing human emotions that are conveyed during conversations. In order to develop a robot that comes close to thinking, acting, and expressing like humans, many researches have been conducted. Among these researches, the proposed method is developed based upon 6 emotion identification systems. The proposed method first analyzes conversations between humans, decides an emotion on the basis of the analysis, and represents the emotion by an action, an image, and a sound. We implemented the proposed method using a hand-sized robot.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37C no.9
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• pp.802-810
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• 2012

This paper describes RFID(Radio Frequency Identification) based target acquisition and docking system. RFID is non-contact identification system, which can send relatively large amount of information using RF signal. Robot employing RFID reader can identify neighboring tag attached objects without any other sensing or supporting systems such as vision sensor. However, the current RFID does not provide spatial information of the identified object, the target docking problem remains in order to execute a task in a real environment. For the problem, the direction sensing RFID reader is developed using a dual-directional antenna. The dual-directional antenna is an antenna set, which is composed of perpendicularly positioned two identical directional antennas. By comparing the received signal strength in each antenna, the robot can know the DOA (Direction of Arrival) of transmitted RF signal. In practice, the DOA estimation poses a significant technical challenge, since the RF signal is easily distorted by the surrounded environmental conditions. Therefore, the robot loses its way to the target in an electromagnetically disturbed environment. For the problem, the g-filter based error correction algorithm is developed in this paper. The algorithm reduces the error using the difference of variances between current estimated and the previously filtered directions. The simulation and experiment results clearly demonstrate that the robot equipped with the developed system can successfully dock to a target tag in obstacles-cluttered environment.

• Journal of Institute of Control, Robotics and Systems
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• v.10 no.5
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• pp.395-401
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• 2004

We present an AILC(Adaptive Iterative Learning Control) scheme and a sufficient condition for system parameter identification for uncertain robotic systems that perform the same tasks repetitively. It is guaranteed that the joint velocity and position asymptotically converge to the reference joint velocity and position, respectively. In addition, it is proved that a sufficient condition for parameter identification is the PE(Persistent Excitation) condition on the regressor matrix evaluated at the reference trajectory during the operation period. Since the regressor matrix on the reference trajectory can be easily computed prior to the real robot operation, the proposed algorithm provides a useful method to verify whether the parameter error converges to zero or not.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2007.10a
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• pp.289-292
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• 2007

An object color identification and classification embedded system realization for uninhabited stock management is presented in this paper. The embedded system is realized by using ultrasonic sensor to extract the object and distance, and detecting binary image from USB CCD camera. The algorithm is identified by comparing the reference pattern with the color pattern of input image, and move to the settled rack at the store. The experimental result leads to use the uninhibited stock management with practice as a robot.

• The Journal of Korea Robotics Society
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• v.4 no.3
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• pp.201-209
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• 2009

In this paper, we deal with the performance evaluation method of user identification and user tracking for intelligent robots using face images. This paper shows general approaches for standard evaluation methods to improve intelligent robot systems as well as their algorithms. The evaluation methods proposed in this paper can be combined with the evaluation methods for detection algorithms of face region and facial components to measure the overall performance of face recognition in intelligent robots.

• Journal of the Korean Society for Precision Engineering
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• v.11 no.1
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• pp.80-88
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• 1994

In the automation of rigid parts mating process with the intelligent robots, Peg-In-Hole is the most available task since inserting is some analytic and needs suitable range of forces that can be controlled by induatrial manipulators. In this Peg-In-Hole process, it is very important to identify the contact state between tow parts, peg and hole, to build the strategies for robot motion that leads to avoid the jamming condition occurs during insertion process. In this paper, we adpopted 3 parameters for identification, lFzl, lFxy/Fzl, and lMxy/Fxyl, derived from axes value of Whitney's jamming diagram. Also, we defined the fuzzy membership functions for these parameters and developed the identification algorithm based on fuzzy inference method of max-product. As an experimental result, we obtained about 96% of identification ratio that could be raised up to industrial requirements by further research.

• Journal of Internet Computing and Services
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• v.14 no.6
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• pp.9-18
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• 2013

In this paper, we design and implement an intelligent system for finding objects with RFID(Radio Frequency IDentification) tag in which an mobile robot can do. The system we developed is a learning system of artificial neural network that uses RSSI(Received Signal Strength Indicator) value as input and absolute coordination value as target. Although a passive RFID is used for location estimation, we consider an active RFID for expansion of recognition distance. We design the proposed system and construct the environment for indoor location estimation. The designed system is implemented with software and the result related learning is shown at test bed. We show various experiment results with similar environment of real one from earning data generation to real time location estimation. The accuracy of location estimation is verified by simulating the proposed method with allowable error. We prepare local test bed for indoor experiments and build a mobile robot that can find the objects user want.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.2
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• pp.214-219
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• 2007

In this paper, a new magnetic position sensing mettled for autonomous vehicle and robot guidance is presented. In autonomous vehicle and robot control, position sensing is an important task for the identification of their locations, such as the current position within a trajectory. The magnet based autonomous vehicle and robot was identified position via magnetic materials. In the magnetic sensing system, the Earth field is one of the largest disturbance. To removal of the Earth field, this paper proposes 1-dimensional magnetic field sensors array and develops precise petition sensing system using linear operating region of the magnetic field sensor. This proposal is verified a feasible magnetic position sensing system for autonomous vehicle and robot guidance by the experimental results.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.37 no.10
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• pp.1219-1227
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• 2013

A new type of wearable robot is developed for a disabled person with disabled limbs, that is, a person who cannot intentionally move his/her legs and arms. This robot can enable the disabled person to grip an object using eye movements. A gaze tracking algorithm is employed to detect pupil movements by which the person observes the object to be gripped. By using this gaze tracking 2D information, the object is identified and the distance to the object is measured using a Kinect device installed on the robot shoulder. By using several coordinate transformations and a matching scheme, the final 3D information about the object from the base frame can be clearly identified, and the final position data is transmitted to the DSP-controlled robot controller, which enables the target object to be gripped successfully.