• Proceedings of the KSME Conference
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• 2008.11a
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• pp.795-800
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• 2008

The paper presents research for the established experiment environment of multi vehicle robot, localization algorithm that is based on vehicle control, and path tracking. The established experiment environment consists of ultrasonic positioning system, vehicle robot, server and wireless module. Ultrasonic positioning system measures positioning for using ultrasonic sensor and generates many errors because of the influence of environment such as a reflection of wall. For a solution of this fact, localization algorithm is proposed to determine a location using vehicle kinematics and selection of a reliable location data. And path tracking algorithm is proposed to apply localization algorithm and LOS, finally, that algorithms are verified via simulation and experimental

• The Journal of Korea Robotics Society
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• v.2 no.3
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• pp.212-220
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• 2007

This paper proposes a method of avoiding obstacles and tracking a moving object continuously and simultaneously by using new concepts of virtual tow point and fuzzy danger factor for differential wheeled mobile robots. Since differential wheeled mobile robot has smaller degree of freedom to control and are non-holonomic systems, there exist multiple solutions (trajectories) to control and reach a target position. The paper proposes 'fuzzy danger factor' for obstacles avoidance, 'virtual tow point' to solve non-holonomic object tracking control problem for unique solution and three kinds of fuzzy logic controller. The fuzzy logic controller is policy decision controller with fuzzy danger factor to decide which controller's result is more valuable when the mobile robot is tracking a moving object with obstacles to be avoided.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.14 no.1
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• pp.17-25
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• 2014

This paper presents the formulation of an impedance controller for regulating the contact force with the environment. To achieve an accurate force tracking control, uncertainties in both robot dynamics and the environment require to be addressed. As part of the framework of the proposed force tracking formulation, a neural network is introduced at the desired trajectory to compensate for all uncertainties in an on-line manner. Compensation at the input trajectory leads to a remarkable structural advantage in that no modifications of the internal force controllers are required. Minimizing the objective function of the training signal for a neural network satisfies the desired force tracking performance. A neural network actually compensates for uncertainties at the input trajectory level in an on-line fashion. Simulation results confirm the position and force tracking abilities of a robot manipulator.

• Proceedings of the KIEE Conference
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• 1999.07g
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• pp.2995-2997
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• 1999

Recently, real-time visual tracking control for a robot manipulator is performed by using a vision feedback sensor information. In this paper, the optical flow is computed based on the eye-in-hand robot configuration. The image jacobian is employed to calculate the rotation and translation velocity of a 3D moving object. LQG visual controller generates the real-time visual trajectory. In order to improving the visual tracking performance. VSC controller is employed to control the robot manipulator. Simulation results show a better visual tracking performance than other method.

• The Journal of Korea Robotics Society
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• v.10 no.2
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• pp.104-111
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• 2015

In this paper, we proposed visual information to provide a highly maneuverable system for a tele-operator. The visual information image is bird's eye view from UFR(Unmanned Flying Robot) shows around UGR(Unmanned Ground Robot). We need UGV detection and tracking method for UFR following UGR always. The proposed system uses TLD(Tracking Learning Detection) method to rapidly and robustly estimate the motion of the new detected UGR between consecutive frames. The TLD system trains an on-line UGR detector for the tracked UGR. The proposed system uses the extended Kalman filter in order to enhance the performance of the tracker. As a result, we provided the tele-operator with the visual information for convenient control.

• Journal of the Korea Institute of Military Science and Technology
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• v.11 no.4
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• pp.141-148
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• 2008

In this paper, we develop a detailed full dynamic model which includes various rough terrains for 6-wheel skid-steering mobile robot based on the real experimental autonomous vehicle called Dog-Horse Robot. We also design a co-simulation for performance comparison of path tracking algorithms. The control architecture in the co-simulation can be divided into two levels. The high level control is the closed-loop control of path tracking to follow a given path, and the low level is concerned about torque control of wheel motion. The simulation using the mechanical data of the Dog-Horse Robot is performed under the Matlab/Simulink environment. We also simulate and evaluate the performance of the model based adaptive controller.

• Journal of the Korean Society of Industry Convergence
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• v.27 no.2_2
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• pp.319-324
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• 2024

In this paper, the Artificial Intelligence Space(AI-Space) for human-robot interface is presented, which can enable human-computer interfacing, networked camera conferencing, industrial monitoring, service and training applications. We present a method for representing, tracking, and objects(human, robot, chair) following by fusing distributed multiple vision systems in AI-Space. The article presents the integration of color distributions into particle filtering. Particle filters provide a robust tracking framework under ambiguous conditions. We propose to track the moving objects(human, robot, chair) by generating hypotheses not in the image plane but on the top-view reconstruction of the scene.

• Proceedings of the Korean Information Science Society Conference
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• 2011.06c
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• pp.405-408
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• 2011

In this paper, we propose a robot remote control system based on mouth tracking. The main idea behind the work is to help disabled people who cannot operate a joystick or keyboard to control a robot with their hands. The mouth detection method in this paper is mainly based on the Adaboost feature detection approach. By using the proposed new Haar-like features for detecting the corner of mouth, the speed and accuracy of detection are improved. Combined with the Kalman filter, a continuous and accurate mouth tracking has been achieved. Meanwhile, the gripping commands of the robot manipulator were also achieved by the recognition of the user.s mouth shape, such as 'pout mouth' or 'grin mouth'. To assess the validity of the method, a mouth detection experiment and a robot cargo transport experiment were applied. The result indicated that the system can realize a quick and accurate mouse tracking; and the operation of the robot worked successfully in moving and bringing back items.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.2
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• pp.125-132
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• 2008

This paper describes a mobile inspection robot with an automatic pipe tracking system for a feeder pipe inspection in a PHWR. The robot is composed of two inch worm mechanisms. One is for a longitudinal motion along a pipe, and the other is for a rotational motion in a circumferential direction to access all of the outer surfaces of a pipe. The proposed mechanism has a stable gripping capability and is easy to install. An automatic pipe tracking system is proposed based on machine vision techniques to make the mobile robot follow an exact outer circumference of a curved feeder pipe as closely as possible, which is one of the requirements of a thickness measurement system for a feeder pipe. The proposed sensing technique is analyzed to attain its feasibility and to develop a calibration method for an accurate measurement. A mobile robot and control system are developed, and the automatic pipe tracking system is tested in a mockup of a feeder pipe.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.7 no.8
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• pp.1759-1766
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• 2003

This paper proposes a neuro­fuzzy controllers for trajectory tracking control of robot manipulators. The computed torque method is an effective means for trajectory tracking control. However, the tracking performance of this method is severely affected by the uncertainties of robot manipulators. Therefore, the proposed controller is used to compensate the uncertainties of robot manipulators. In the neuro­fuzzy controllers, the number of fuzzy rules used forty­nine. The effectiveness of the proposed controllers is demonstrated by computer simulations using two­link robot manipulator, As a result, it is confirmed that the output of the proposed neuro­fuzzy controllers can efficiently decrease the uncertainties of robot manipulator.