• Journal of the Korean Institute of Intelligent Systems
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• v.26 no.1
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• pp.16-22
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• 2016

The research on two-wheeled inverted pendulum (TWIP) mobile robots has been ongoing in a number of robotic laboratories around the world. In this paper, we consider a robust controller design for the TWIP mobile robot driving on uniform slopes. We use a 2 degree-of-freedom (DOF) model which is obtained by restricting the spinning motion in a 3 DOF motion dynamic equation. In order to design the robust controller guaranteeing stability of the TWIP mobile robot driving on inclined surface, we propose a sliding mode control based on the theory of variable structure systems and design a sliding surface using the theory of the linear quadratic regulation (LQR). For simulation, the dynamic model of the TWIP mobile robot is constructed using Mathworks' Simulink and the sliding mode control is also implemented using Simulink. From simulation results, we show that the proposed controller effectively controls the TWIP mobile robot driving on slopes.

• Journal of the Korean Institute of Intelligent Systems
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• v.26 no.1
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• pp.64-69
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• 2016

In this paper, a marathon of a humanoid robot is introduced, and its strategy is proposed. In order to develop humanoid robots for the purpose of cooperation and symbiosis with humans, the technologies such as increasing operating time and stability or recognizing surrounding environment are more important. One proper research model for the technologies is a human's marathon. In this paper, we introduce the human's marathon, and propose the humanoid robot's marathon. The marathon event of HuroCup has the most similar game rules to the human's marathon. The humanoid robot developed with the proper operating time, stability and ability to recognize the surrounding environment performed the marathon in HuroCup. The robot recognizes a marathon track using a computer vision, and builds the strategies for the race competition. By analyzing the experimental results, the humanoid robot performed in a real competition.

• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.4
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• pp.519-524
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• 2009

Recently, reinforcement learning methods have drawn much interests in the area of machine learning. Dominant approaches in researches for the reinforcement learning include the value-function approach, the policy search approach, and the actor-critic approach, among which pertinent to this paper are algorithms studied for problems with continuous states and continuous actions along the line of the actor-critic strategy. In particular, this paper focuses on presenting a method combining the so-called ACFRL(actor-critic fuzzy reinforcement learning), which is an actor-critic type reinforcement learning based on fuzzy theory, together with the RLS-NAC which is based on the RLS filters and natural actor-critic methods. The presented method is applied to a control problem for crawling robots, and some results are reported from comparison of learning performance.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.36 no.10
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• pp.1205-1211
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• 2012

A marionette is a moving puppet that can be made to perform several actions by pulling wires connected to the puppet. Because a marionette is operated by hand, a stage performance with a human-sized marionette is impossible. However, a marionette robot operated using a wire controller could be used as a human-sized marionette to conduct a stage performance with other robots or actors. In addition, by using mobile stages that utilize mobile platforms, a wire controller, and the marionette robot body, the large marionette robot system designed in this study can be made to rotate and translate freely in a stage performance. The feasibility of the structure of the marionette robot wire control system is verified by using dynamics analysis. Furthermore, the efficiency and safety of the robot is demonstrated by manufacturing and operating a prototype robot.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.7
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• pp.901-906
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• 2007

Algorithms of path planning and obstacle avoidance are essential to autonomous mobile robots that are working in unknown environments in the real time. This paper presents a new navigation algorithm for an autonomous mobile robot with vision and IR sensors using fuzzy rules. Temporary targets are set up by distance variation method and then the algorithms of trajectory planning and obstacle avoidance are designed using fuzzy rules. In this approach, several digital image processing technique is employed to detect edge of obstacles and the distances between the mobile robot and the obstacles are measured. An autonomous mobile robot with single vision and IR sensors is built up for experiments. We also show that the autonomous mobile robot with the proposed algorithm is navigating very well in complex unknown environments.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.2
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• pp.251-256
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• 2008

Many researchers are studying about human Brain-Computer Interface(BCI) that it based on electroencephalogram(EEG) signals of multichannel. The researches of EEG signals are used for detection of a seizure or a epilepsy and as a lie detector. The researches about an interface between Brain and Computer have been studied robots control and game of using human brain as engineering recently. Especially, a field of brain studies used EEG signals is put emphasis on EEG artifacts elimination for correct signals. In this paper, we measure EEG signals as human emotions and divide it into five frequence parts. They are calculated related the percentage of selecting range to total range. the calculating values are compared standard values by Bayesian Network. lastly, we show the human face avatar as human Emotion.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.2
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• pp.163-168
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• 2008

Navigation system based on indoor location estimation is one of the core technologies in mobile robot systems. Wireless sensor network has great potential in the indoor location estimation due to its characteristics such as low power consumption, low cost, and simplicity. In this paper we present an algorithm to estimate the indoor location of mobile robot based on wireless sensor network and fuzzy modeling. ZigBee-based sensor network usually uses RSSI(Received Signal Strength Indication) values to measure the distance between two sensor nodes, which are affected by signal distortion, reflection, channel fading, and path loss. Therefore we need a proper correction method to obtain accurate distance information with RSSI. We develop the fuzzy distance models based on RSSI values and an efficient algorithm to estimate the robot location which applies to the navigation algorithm incorporating the time-varying data of environmental conditions which are received from the wireless sensor network.

• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.5
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• pp.477-481
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• 2014

Human has various types of emotions which affect speculation, judgement, activity, and the like at the moment. Specifically, walking is also affected by emotions, because one's emotion status can be easily inferred by his or her walking style. The present research on biped walking with humanoid robots is mainly focused on stable walking irrespective of ground condition. For effective human-robot interaction, however, walking pattern needs to be changed depending on the emotion status of the robot. This paper provides analysis and comparison of gait experiment data for the men and women in four representative emotion states, i.e., joy, sorrow, ease, and anger, which was acquired by a gait analysis system. The data and analysis results provided in this paper will be referenced to emotional biped walking of a humanoid robot.

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.5
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• pp.570-576
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• 2012

In this research a moving platform for a mobile robot which can run with upright posture is proposed. It is able to stand with standing arms and run uprightly based on an inverted pendulum mechanism. Conventional mobile robots generally may equip 4 wheels or 3 wheels including a caster and have good statistic stability. They need a steering mechanism to choose which way to go since they have a square or rectangular configuration with multiple wheels. When a mobile robot meets a sharply perpendicular and narrow crossroad, it may need a special steering scheme such as going forward and backward repeatedly or it sometimes cannot even pass through the crossroad because of its size. The proposed moving platform for a mobile robot changes to a upright posture which has a small planar area and is able to pass through the crossroad. We propose a moving platform for a mobile robot with a inverted pendulum mechanism and standing arms which can make the mobile robot upright.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.1
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• pp.20-26
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• 2008

As they have more and more intelligence robots or computers these days, so the interaction between intelligence robot(computer) - human is getting more and more important also the emotion recognition and expression are indispensable for interaction between intelligence robot(computer) - human. In this paper, firstly we extract emotional features at speech signal and facial image. Secondly we apply both BL(Bayesian Learning) and PCA(Principal Component Analysis), lastly we classify five emotions patterns(normal, happy, anger, surprise and sad) also, we experiment with decision fusion and feature fusion to enhance emotion recognition rate. The decision fusion method experiment on emotion recognition that result values of each recognition system apply Fuzzy membership function and the feature fusion method selects superior features through SFS(Sequential Forward Selection) method and superior features are applied to Neural Networks based on MLP(Multi Layer Perceptron) for classifying five emotions patterns. and recognized result apply to 2D facial shape for express emotion.