• Journal of Institute of Control, Robotics and Systems
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• v.16 no.7
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• pp.674-680
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• 2010

It is known that many insects and animals can return to their nest after exploration, with their own specific homing mechanisms. Their homing navigation methods have been applied to the robotic navigation. In this paper, we test the sector-based image matching method motivated by the honeybee's landmark navigation behaviour. Here, our robotic approach uses the reference compass to identify the current head direction and the relative angular position of landmarks for the navigation. The robot shows desirable homing behaviors if the robot is surrounded by landmarks. The result of robot experiment is in good agreement with that of simulation.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.11
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• pp.883-887
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• 2016

Navigating an unknown environment is a challenging task for a robot, especially when a large number of obstacles exist and the odometry lacks reliability. Pose tracking allows the robot to determine its location relative to its previous location. The ICP (iterative closest point) has been a powerful method for matching two point clouds and determining the transformation matrix between the maps. However, in a situation where odometry is not available and the robot moves far from its original location, the ICP fails to calculate the exact displacement. In this paper, we suggest a method that is able to match two different point clouds taken a long distance apart. Without using any odometry information, it only exploits the features of corner points containing information on the surroundings. The algorithm is fast enough to run in real time.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.11
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• pp.952-959
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• 2016

This paper proposes a novel indoor positioning system (IPS) that uses a calibrated camera sensor network and dense 3D map information. The proposed IPS information is obtained by generating a bird's-eye image from multiple camera images; thus, our proposed IPS can provide accurate position information when objects (e.g., the mobile robot or pedestrians) are detected from multiple camera views. We evaluate the proposed IPS in a real environment with moving objects in a wireless camera sensor network. The results demonstrate that the proposed IPS can provide accurate position information for moving objects. This can improve the localization performance for mobile robot operation.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.03a
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• pp.127-130
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• 1998

In this paper, we propose a method of cooperative control(T-cell modeling) and selection of group behavior strategy(B-cell modeling) based on immune system in distributed autonomous robotic system(DARS). Immune system is living body's self-protection and self-maintenance system. Thus these features can be applied to decision making of optimal swarm behavior in dynamically changing environment. For the purpose of applying immune system to DARS, a robot is regarded as a B cell, each environmental condition as an antigen, a behavior strategy as an antibody and control parameter as a T-call respectively. The executing process of proposed method is as follows. When the environmental condition changes, a robot selects an appropriate behavior strategy. And its behavior strategy is stimulated and suppressed by other robot using communication. Finally much stimulated strategy is adopted as a swarm behavior strategy. This control scheme is based of clonal selection and idiotopic network hypothesis. And it is used for decision making of optimal swarm strategy. By T-cell modeling, adaptation ability of robot is enhanced in dynamic environments.

• Journal of the Korean Institute of Intelligent Systems
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• v.13 no.5
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• pp.590-595
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• 2003

In this paper, we propose a new method to the speed control of soccer robot using messy Genetic Algorithm(mGA). In order to arrive in the target of the soccer robot within the smallest time ,we propose the speed control function with several parameters which represent the reflection ratio distance and angle error. Also, we propose the algorithm for searching these parameters by using messy Genetic Algorithm. As a result of finding the optimal parameters, we can move the robot the most quickly in the target under the complex environment.

• Journal of the Ergonomics Society of Korea
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• v.7 no.1
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• pp.31-37
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• 1988

This paper designs, in the teleoperation task, the world coordinate system by the functional analysis of each of the robot joint so that the human operator performs easily the task. Also, it constructs the heuristic rules of the equal motion line coordinates for the position and the posture control of the robot within the knowledge base so that the robot hand reaches-possibly in any position of the robot's work space. As shown in the result of the experiments. the coordinate reading is easy because the work station is displayed to the high resolution by using the superimposer of the motion analysing computer system. Also. the task burden of the human operator reduces and the error recovery time reduces because the coordinates of the object is obtained just by touch using the digitizer.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2002.10a
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• pp.256-261
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• 2002

In this paper, it is presented a new scheme of adaptive-neuro control system to implement real-time control of robot manipulator. Unlike the well-established theory for the adaptive control of linear systems, there exists relatively little general theory for the adaptive control of nonlinear systems. Adaptive control technique is essential for providing a stable and robust performance for application of robot control. The proposed neuro control algorithm is one of learning a model based error back-propagation scheme using Lyapunov stability analysis method. Through simulation, the proposed adaptive-neuro control scheme is proved to be a efficient control technique for real-time control of robot system using DSPs.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.4
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• pp.337-343
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• 2005

In this paper, experimental studies of force control of the crack tracking robot are presented. The crack tracking robot should maintain constant contact with the road to perform cleaning process of the crack effectively. Regulating desired force on the road requires a sophisticated force control algorithm. Here, two main force control algorithms such as the impedance force control and the explicit force control are used. Performances of two force control algorithms are compared.

• Journal of Institute of Control, Robotics and Systems
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• v.12 no.9
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• pp.861-867
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• 2006

This paper presents the robust mobile robot localization method exploiting redundant motion information acquired from three optical mice that are installed at the bottom of a mobile robot in a regular triangular form. First, we briefly introduce a low-cost optical motion sensor, HDNS-2000, and a commercial device driver development tools, WinDriver, to be used in this research. Second, we explain the basic principle of the mobile robot localization using the motion information from three optical mice, and propose the least squares based localization algorithm which is robust to the noisy measurement and partial malfunctioning of optical mice. Third, we describe the development of the experimental optical odometer using three PC optical mice and the user-friendly graphic monitoring program. Fourth, simulations and experiments are performed to demonstrate the validity of the proposed localization method and the operation of the developed optical odometer. Finally, along with the conclusion, we suggest some future work including the installation parameter calibration, the optical mouse remodelling, and the high-performance motion sensor adoption.

• Journal of Institute of Control, Robotics and Systems
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• v.9 no.7
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• pp.515-526
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• 2003

Tutorial contents of kinematics and dynamics of a wheeled drive mobile robot are presented. Based on the dynamic model, simulation studies of position tracking of a mobile robot are performed. The control structure of several position control algorithms using visual feedback are proposed and their performances are compared. In order to compensate for uncertainties from unknown dynamics and ignored dynamic effects such as slip conditions, neural network based position control schemes are proposed. Experiments are conducted and the results show the performance of the vision based neural network control scheme fumed out to be the best among several proposed schemes.