• Journal of the Korean Institute of Intelligent Systems
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• v.13 no.2
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• pp.186-191
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• 2003

Skills in tracing of the MR divide into following, approaching, avoiding and warning and so on. It is difficult to have all these skills learned as neural network. To make this up for, skills consisted of each module, and Mobile Robot was controlled by the output of module adequate for the situation. A mobile Robot was equipped multi-ultrasonic sensor and a USB Camera, which can be in place of human sense, and the measured environment information data is learned through Modular Neural Network. MNN consisted of optimal combination of activation function in the Expert Network and its structure seemed to improve learning time and errors. The Gating Network(GN) used to control output values of the MNN by switching for angle and speed of the robot. In the paper, EN of Modular Neural network was designed optimal combination. Traveling with a real MR was performed repeatedly to verity the usefulness of the MNN which was proposed in this paper. The robot was properly controlled and driven by the result value and the experimental is rewarded with good fruits.

• Journal of the Korean Institute of Intelligent Systems
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• v.26 no.3
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• pp.176-181
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• 2016

In this paper, the autonomous mobile robot control system for detecting fire was proposed using the wearable device based on EMG(Electromyogram) signal. Myo armband is used for detecting the user's EMG signal. The gesture was classified after sending the data of EMG signal to a computer using Bluetooth communication. Then the robot named 'uBrain' was implemented to move by received data from Bluetooth communication in our experiment. 'Move front', 'Turn right', 'Turn left', and 'Stop' are controllable commands for the robot. And if the robot cannot receive the Bluetooth signal from a user or if a user wants to change manual mode to autonomous mode, the robot was implemented to be in the autonomous mode. The robot flashes the LED when IR sensor detects the fire during moving.

• Journal of the Korean Institute of Intelligent Systems
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• v.16 no.4
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• pp.389-395
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• 2006

This paper proposes the controller for biped robot using intelligent control algorithm. In order to simplify the complexity of biped robot control, manipulator of biped robot is divided into four modules. These modules are controlled by intelligent algorithm with Hierarchical Mixture of Experts(HME) using neural network. Also neural network having direct control method learns the inverse dynamics of biped robot. The HME, which is a network of tree structure, reallocates the input domain for the output by learning pattern of input and output. In this paper, as a result of learning HME repeatedly with EM algorithm, the controller for biped robot operating safety walking is designed by modelling dynamics of biped robot and generating virtual error of HME.

• Journal of the Korean Institute of Intelligent Systems
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• v.16 no.4
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• pp.485-492
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• 2006

This paper deals with implementation of network for distributed control system of a humanoid robot ISHURO(Inha Semyung Humanoid Robot). A humanoid robot needs much degree of freedom structurally and much data for having flexible movement. To realize such a humanoid robot, distributed control method is preferred to the centralized one since it gives a compactness, modularity and flexibility for the controllers. For organizing distributed control system of a humanoid robot, a control processor on a board is needed to individually control the joint motor and communication technology between the processors is required to transmit its information within control time. The processor is DSP-based processor and includes CAN network on a chip. It shares the computational load such as monitoring the sensor information and controlling the actuator between each of modules. In this paper, the communication architecture is suggested and its message protocol are discussed including message structure, time consumption for transmission, and controller structure at the view of distributed control for a humanoid robot. All of the sequence are simulated with Matlab and then verified with real walking experiment by ISHURO.

• Journal of the Korean Institute of Intelligent Systems
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• v.16 no.4
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• pp.443-448
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• 2006

In this paper, a novel method is proposed for generating the low-power and stable walking trajectory of biped robots, and then a biped robot with 25 DOFs(degrees of freedom) is designed and implemented for the realization of the low-power walking trajectory generated by the proposed method. In our method, first a stable VPCG(vertically projected center of gravity) trajectory is generated, and then the trajectories of ankle and pelvis of a biped robot are planned to follow the preplanned stable VPCG trajectory, which produces a waking pattern without bending its knees and enables a biped robot to walk with less power consumption. On the other hand, a biped robot implemented in this paper has the mechanical structure of foot that enables a biped robot to support on the ground well, and the mechanical structure of pelvis that enables a biped robot to move flexibly. From results of the walking experiment and power consumption measurement, it was confirmed that the proposed method can generate the more stable and flexible trajectory with less power consumption compared with the existing methods which do not use the ankle of a biped robot.

• Journal of the Korean Society for Precision Engineering
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• v.13 no.2
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• pp.76-83
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• 1996

We have developed the unconventional robot arm which is composed of the two main parts, one is a ball screw and the other is a robot arm. The dynamic systems of the robot arm and ball screw are unstable systems coupled with each other. The ball screw mechanism is unstable system but controllable system. The robot arm's dynamics is quasi stable system when ball screw's angular position is zero, else, unstable system. Our system has the duality between stability and controllability at the view point of control. This duality causes difficulty to control of the robot arm using normal control law. We have investigated the location of the characteristic roots of the dynamic equation. And we have found out that the best condition for the control of the arm is quasi stable state. In this paper, we have proposed multiple control laws which are consist of three components to guarantee the stability and controllability simultaneously. The computer simulations were carried out based on VSC about the angular position control of the robot arm, and it is confirmed that the good performances could be obtained by using new controller.

• Journal of Korea Society of Industrial Information Systems
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• v.13 no.4
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• pp.145-154
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• 2008

In this paper, we propose the pet robot control system using hand gesture recognition in image sequences acquired from a camera affixed to the pet robot. The proposed system consists of 4 steps; hand detection, feature extraction, gesture recognition and robot control. The hand region is first detected from the input images using the skin color model in HSI color space and connected component analysis. Next, the hand shape and motion features from the image sequences are extracted. Then we consider the hand shape for classification of meaning gestures. Thereafter the hand gesture is recognized by using HMMs (hidden markov models) which have the input as the quantized symbol sequence by the hand motion. Finally the pet robot is controlled by a order corresponding to the recognized hand gesture. We defined four commands of sit down, stand up, lie flat and shake hands for control of pet robot. And we show that user is able to control of pet robot through proposed system in the experiment.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.2
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• pp.86-92
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• 2007

This paper presents the development of fire-fighting and rescue robot for Outdoor Environment. In the procedure of this development, we follow Target Oriented Design (TOD) which is recognized as the systematic methodology to design a system by specifying the target clearly. For some real fire fighting tasks (e.g. tasks in shopping street and a market), narrow road make it difficult for existing fire engine to access the firing place. On the other hand, for dangerous tasks (e.g. gasoline station and a storehouse) the explosive materials make it impossible for fire-fighters to access the firing place. Moreover, the smoke and the high-temperature caused by fire make fire fighting difficult. In this situation, the solution is to develop the fire-fighting and rescue robot. TOD is performed firstly by analyzing the environment properties of fro place and the demanded tasks and the fire-fighting and rescue robot is manufactured. For safety, the fire fighting robot should be controlled by remote operation to keep the operator away from the fire, and the control system is divided into three parts: the robot controllers, controller for remote operating device and wireless communication system. We have selected and developed appropriate hardware and software for each part of control system with considering TOD. As a result, the fire-fighting robot functions correctly and the performance and usefulness of our control architecture is validated by successfully performing some fire-fighting tasks.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.11
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• pp.1068-1073
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• 2010

When a robot navigates in an outdoor environment, a curb or a sidewalk separated from the road can be used as a robust feature. However, most algorithms could detect the curb only in the straight road, and could not detect highly curved corners, ramps, and so on. This paper proposes an algorithm which enables the robot to detect and follow the curbs in various types of roads. In the proposed method, the robot tilts a laser scanner and computes the error between the predicted and the measured distances to the road in front of the robot. Based on this error, the curbs at corners and curves can be classified. It is also difficult to detect a curb near a ramp because of its low height. In this case, the robot also tilts a laser scanner to detect the curb beyond the ramp. Once the robot classifies the road into the curve, corner, ramp, the robot selects the proper navigation strategies depending on the classified road types and is able to continue to detect and follow the curb. The results of a series of experiments show that the robot can stably detect and follows the curb in curves, corners and ramps as well as the straight road.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.8
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• pp.753-757
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• 2015

This paper introduces an experimental rescue robot, HUBO T-100 and presents the optimal motion control method. The objective of the rescue robot is to extract patients or wounded soldiers in the battlefield and hazardous environments. Another mission is to dispose and transport an explosive ordnance to safe places. To execute these missions, the upper body of the rescue robot is humanoid in form to execute various kinds of tasks. The lower body features a hybrid tracked/legged design, which allows for a variety of mode of locomotion, depending on terrain conditions in order to increase traversability. The weight lifting motion is one of the most important task for performing rescue related missions because the robot must lift an object or impaired person lying on the ground for transferring. Here, dynamics based motion optimization is employed to minimize joint torques while maintaining stability simultaneously. Physical experiments with a real humanoid robot, HUBO T-100, are presented to verify the proposed method.