• Journal of the Korean Institute of Intelligent Systems
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• v.26 no.4
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• pp.253-258
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• 2016

This paper proposes a method that utilizes optimization approach for localization of an indoor mobile robot. Bayesian filters which have been widely used for localization of a mobile robot use many control parameters to take the uncertainties in measurement and environment into account. The estimation performance depends on the selection of these parameter values. Also, the performance of the Bayesian filters deteriorate as the non-linearity of the motion and measurement increases. On the other hand, the optimization approach uses fewer control parameters and is less influenced by the non-linearity than the Bayesian methods. This paper compares the localization performance of the proposed method with the performance of the extended Kalman filter to verify the feasibility of the proposed method. Measurements of ranges from beacons of ultrasonic satellite to the robot are used for localization. Mahalanobis distance is used for detection and rejection of outlier in the measurements. The optimization method sets performance index as a function of the measured range values, and finds the optimized estimation of the location through iteration. The method can improve the localization performance and reduce the computation time in corporation with Bayesian filter which provides proper initial location for the iteration.

• Journal of the Korean Institute of Intelligent Systems
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• v.16 no.2
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• pp.215-221
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• 2006

This paper is concerned with the control of multiple nonlinearities included in a humanoid robot system. A humanoid robot has some problems such as the structural instability, which leads to consider the control of multiple nonlinearities caused by driver parts as well as gear reducer. Saturation and backlash are typical examples of nonlinearities in the system. The conventional algorithms of backlash control were fuzzy algorithm, disturbance observer and neural network, etc. However, it is not easy to control the system by employing only single algorithm since the system usually includes multiple nonlinearities. In this paper, a switching Pill is considered for a control of saturation and a dual feedback algorithm is proposed for a backlash control. To implement the above algorithms, the system identification is firstly performed for the minimization of the difference between the results of simulation and experiment, and then the switching Pill gains are determined using genetic algorithm with some heuristic approach. The performance of the switching Pill controller for saturation and the dual feedback for backlash control is investigated through the simulation. Finally, it is shown that the implemented control system has good results and can be applied to the real humanoid robot system ISHURO.

• Journal of Korea Society of Industrial Information Systems
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• v.24 no.5
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• pp.115-120
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• 2019

In this paper, we present the results of the performance statistical analysis of the multi-robot formation control based on receding horizon particle swarm optimization (RHPSO). The formation control problem of multi-robot system can be defined as a constrained nonlinear optimization problem when considering collision avoidance between robots. In general, the constrained nonlinear optimization problem has a problem that it takes a long time to find the optimal solution. The RHPSO algorithm was proposed to quickly find a suboptimal solution to the optimization problem of multi-robot formation control. The computational complexity of the RHPSO increases as the number of candidate solutions and generations increases. Therefore, it is important to find a suboptimal solution that can be used for real-time control with minimal candidate solutions and generations. In this paper, we compared the formation error according to the number of candidate solutions and the number of generations. Through numerical simulations under various conditions, the results are analyzed statistically and the minimum number of candidate solutions and the minimum number of generations of the RHPSO algorithm are derived within the allowable control error.

• The Transactions of the Korea Information Processing Society
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• v.13 no.8
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• pp.356-366
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• 2024

Users of intelligent robots require access to the status data of the robots for various reasons. The status data of intelligent robots can be generated by combining the status data of the functional agents that constitute the intelligent robot. However, existing intelligent robot systems do not generate the necessary agent status data for creating the status data of intelligent service robots, or they generate it in different ways, making it impossible to collect this information in a uniform manner. Furthermore, these systems have limitations such as collecting the same information redundantly if multiple users request it and only using a single method of communication to deliver robot information, thereby failing to offer the communication methods desired by users. This paper proposes a multi-agent monitoring system for intelligent service robots designed to overcome these limitations. This monitoring system generates status data in response to the actions performed by functional agents, thereby allowing for the unified generation and collection of agent status data. Additionally, the monitoring system resolves data redundancy issues by collecting the necessary data just once, in accordance with user monitoring demands, and delivers status data through a proxy that supports the preferred communication methods of users, thereby providing compatibility with various communication methods. Through experiments, we have verified that this monitoring system can deliver the status data of intelligent robots to multiple users using various communication methods.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.2
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• pp.208-213
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• 2007

As recent research on home service robot has been performed actively in these days. It becomes very important for the robot to react upon voice and sound source, and then tracks an object position in dynamic environment like a home. When people choose a path for finding a destination of objects, in case of sound, they track a direction of the sound source. Or in case as a position of the object be girded with a point on map, people track the position according to absolute orientation of the present position and the sound source position. In this paper, In this manner we had views on what people decide own direction when they react one's voice or go some directions. We suggest a algorithm that intelligent mobile robots on which we installed a sound source tracking board and a digital magnetic compass board go some object's positions by the direction of sound source and absolute orientation.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.8
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• pp.709-717
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• 2013

This paper presents the development of a specialized underwater leg with a manipulator function(convertible-to-arm leg) for the seabed walking robot named CRABSTER200(CR200). The objective functions of the convertible-to-arm leg are to walk on the seabed and to work in underwater for precise seabed exploration and underwater tasks under coastal area with strong tidal current. In order to develop the leg, important design elements including the degree of freedom, dimensions, mass, motion range, joint structure/torque/angular-speed, pressure-resistance, watertight capability and cable protection are considered. The key elements of the convertible-to-arm leg are realized through concept/specific/mechanical design and implementation process with a suitable joint actuator/gear/controller selection procedure. In order to verify the performance of the manufactured convertible-to-arm leg, a 25bar pressure-resistant and watertight test using a high-pressure chamber and a joints operating test with posture control of the CR200 are performed. This paper describes the whole design, realization and verification process for implementation of the underwater convertible-to-arm leg.

• Journal of Institute of Control, Robotics and Systems
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• v.12 no.3
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• pp.208-220
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• 2006

Energy of wheeled mobile robot is usually supplied by batteries. In order to extend operation time of mobile robots, it is necessary to minimize the energy consumption. The energy is dissipated mostly in the motors, which strongly depends on the velocity profile. This paper investigates various 3-step (acceleration - cruise - deceleration) speed control methods to minimize a new energy object function which considers the practical energy consumption dissipated in motors related to motor control input, velocity profile, and motor dynamics. We performed an analysis on the energy consumption various velocity profile patterns generated by standard control input such as step input, ramp input, parabolic input, and exponential input. Based on these standard control inputs, we analyzed the six 3-step velocity profile patterns: E-C-E, P-C-P, R-C-R, S-C-S, R-C-S, and S-C-R (S means a step control input, R means a ramp control input, P means a parabolic control input, and E means an exponential control input, C means a constant cruise velocity), and suggested an efficient iterative search algorithm with binary search which can find the numerical solution quickly. We performed various computer simulations to show the performance of the energy-optimal 3-step speed control in comparison with a conventional 3-step speed control with a reasonable constant acceleration as a benchmark. Simulation results show that the E-C-E is the most energy efficient 3-step velocity profile pattern, which enables wheeled mobile robot to extend working time up to 50%.

• Journal of Korea Multimedia Society
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• v.8 no.10
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• pp.1337-1346
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• 2005

In this paper, we describe an algorithm which can automatically recognize human gesture for Human-Robot interaction. In early works, many systems for recognizing human gestures work under many restricted conditions. To eliminate these restrictions, we have proposed the method that can represent 3D and 2D gesture information simultaneously, APM. This method is less sensitive to noise or appearance characteristic. First, the feature vectors are extracted using APM. The next step is constructing a gesture space by analyzing the statistical information of training images with PCA. And then, input images are compared to the model and individually symbolized to one portion of the model space. In the last step, the symbolized images are recognized with HMM as one of model gestures. The experimental results indicate that the proposed algorithm is efficient on gesture recognition, and it is very convenient to apply to humanoid robot or intelligent interface systems.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.6
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• pp.155-164
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• 2004

Recently, we have remarkable developments in intelligent robot systems. The remarkable features of intelligent robot are that it can track user and is able to doface recognition, which is vital for many surveillance-based systems. The advantage of face recognition compared with other biometrics recognition is that coerciveness and contact that usually exist when we acquire characteristics do not exist in face recognition. However, the accuracy of face recognition is lower than other biometric recognition due to the decreasing in dimension from image acquisition step and various changes associated with face pose and background. There are many factors that deteriorate performance of face recognition such as thedistance from camera to the face, changes in lighting, pose change, and change of facial expression. In this paper, we implement a new sliding active camera system to prevent various pose variation that influence face recognition performance andacquired frontal face images using PCA and HMM method to improve the face recognition. This proposed face recognition algorithm can be used for intelligent surveillance system and mobile robot system.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.5
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• pp.577-582
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• 2004

This paper describes position estimation algorithm using neural network for the navigation of the vision-based Wheeled Mobile Robot (WMR) in a corridor with taking ceiling lamps as landmark. From images of a corridor the lamp's line on the ceiling in corridor has a specific slope to the lateral position of the WMR. The vanishing point produced by the lamp's line also has a specific position to the orientation of WMR. The ceiling lamps has a limited size and shape like a circle in image. Simple image processing algorithms are used to extract lamps from the corridor image. Then the lamp's line and vanishing point's position are defined and calculated at known position of WMR in a corridor To estimate the lateral position and orientation of WMR from an image, the relationship between the position of WMR and the features of ceiling lamps have to be defined. Data set between position of WMR and features of lamps are configured. Neural network are composed and teamed with data set. Back propagation algorithm(BPN) is used for learning. And it is applied in navigation of WMR in a corridor.