• Journal of Institute of Control, Robotics and Systems
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• v.11 no.5
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• pp.398-405
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• 2005

The intelligent robots that will be needed in the near future are human-friendly robots that are able to coexist with humans and support humans effectively. To realize this, robots need to recognize their position and posture in known environment as well as unknown environment. Moreover, it is necessary for their localization to occur naturally. It is desirable for a robot to estimate of his position by solving uncertainty for mobile robot navigation, as one of the best important problems. In this paper, we describe a method for the localization of a mobile robot using image information of a moving object. This method combines the observed position from dead-reckoning sensors and the estimated position from the images captured by a fixed camera to localize a mobile robot. Using a priori known path of a moving object in the world coordinates and a perspective camera model, we derive the geometric constraint equations which represent the relation between image frame coordinates for a moving object and the estimated robot's position. Also, the control method is proposed to estimate position and direction between the walking human and the mobile robot, and the Kalman filter scheme is used for the estimation of the mobile robot localization. And its performance is verified by the computer simulation and the experiment.

• 제어로봇시스템학회:학술대회논문집
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• 1988.10b
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• pp.810-815
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• 1988

This paper presents a mobile robot that travels employing visual information. The mobile robot is equipped solely with a TV camera as a sensor, and views from the TV camera are transferred to a separately installed micro computer through an image acquisition device. An acquired image of a view is processed there and the information necessary for travel is yielded. Instructions based on the information are then sent from the micro computer to the mobile robot, which causes the mobile robot next action. Among several application programs that have already been developed for the mobile robot other than the entire control program, this paper focuses its attention on the travelling control of the mobile robot in a model environment with obstructions as well as an overview of the whole system. The behaviour the present mobile robot takes when it travels among obstructions was investigated by an experiment, and satisfactory results were obtained.

• Proceedings of the IEEK Conference
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• 2002.07c
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• pp.1889-1892
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• 2002

In this paper, we propose the self-autonomous algorithm for mobile robot system (MRS). The proposed mobile robot system which is learned by learning with the neural network can trace the target at the same distances. The mobile robot can use ultrasonic sensors and calculate the distance between target and mobile robot. By teaming the setup distance, current distance and command velocity, the robot can do intelligent self-autonomous drive. We use the neural network and back-propagation algorithm as a tool of learning. As a result, we confirm the ability of tracing the target with proposed mobile robot.

• Journal of the Korean Society for Precision Engineering
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• v.17 no.8
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• pp.189-197
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• 2000

This paper addresses that the autonomous mobile robot with the function of teaching a moving path by speech and avoiding a collision is developed. The use of human speech as the teaching method provides more convenient user-interface for a mobile robot. In speech recognition system a speech recognition algorithm using neural is proposed to recognize Korean syllable. For the safe navigation the autonomous mobile robot needs abilities to recognize a surrounding environment and to avoid collision with obstacles. To obtain the distance from the mobile robot to the various obstacles in surrounding environment ultrasonic sensors is used. By the navigation algorithm the robot forecasts the collision possibility with obstacles and modifies a moving path if it detects a dangerous obstacle.

• Journal of the Korean Institute of Intelligent Systems
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• v.12 no.1
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• pp.27-32
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• 2002

This paper describes a fuzzy steering controller for an outdoor autonomous mobile robot using MR(magneto-resistive) sensor. Using the magnetic field difference values(dBy, dBz) obtained from the MR sensor, we designed fuzzy logic controller for driving the robot on the road center and proposed a method to eliminate the Earth magnetic field. To develop an autonomous mobile robot simulation program, we have done modeling MR sensor, mobile robot and coordinate transformation. A computer simulation of the robot including mobile robot dynamics and steering was used to verify the driving performance of the mobile robot controller using the fuzzy logic. So, we confirmed the robustness of the proposed fuzzy controller by computer simulation.

• IEMEK Journal of Embedded Systems and Applications
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• v.15 no.6
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• pp.281-287
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• 2020

In this paper, we propose a method for estimating a walking direction by which a mobile robots follows a person using TRT (Tensor RT) pose, which is motion recognition based on deep learning. Mobile robots can measure individual movements by recognizing key points on the person's pelvis and determine the direction in which the person tries to move. Using these information and the distance between robot and human, the mobile robot can follow the person stably keeping a safe distance from people. The TRT Pose only extracts key point information to prevent privacy issues while a camera in the mobile robot records video. To validate the proposed technology, experiment is carried out successfully where human walks away or toward the mobile robot in zigzag form and the robot continuously follows human with prescribed distance.

• The Journal of Korea Robotics Society
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• v.5 no.1
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• pp.23-31
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• 2010

This paper suggests a multiple robot simulator which considers the uncertainties in robot motion and sensing. A mobile robot moves with errors due to some kinds of uncertainties from actuators, wheels, electrical components, environments. In addition, sensors attached to a mobile robot can't make accurate output information because of uncertainties of the sensor itself and environment. Uncertainties in robot motion and sensing leads researchers find difficulty in building mobile robot navigation algorithms. Generally, a robot algorithm without considering unexpected uncertainties fails to control its action in a real working environment and it leads to some troubles and damages. Thus, the authors propose a simulator model which includes robot motion and sensing uncertainties to help making robust algorithms. Sensor uncertainties are applied in range sensors which are widely used in mobile robot localization, obstacle detection, and map building. The paper shows performances of the proposed simulator by comparing it with a simulator without any uncertainty.

• Transactions on Control, Automation and Systems Engineering
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• v.3 no.4
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• pp.223-228
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• 2001

We have been developed an intelligent mobile robot with an artificial olfactory function to recognize odours and to track odour source location. This mobile robot also has ben installed an engine for speech recognition and synthesis and is controlled by wireless communication. An artificial olfactory system based on array of 7 gas sensors has been installed in the mobile robot for odour recognition, and 11 gas sensors also are located in the obttom of robot to track odour sources. 3 optical sensors are also in cluded in the intelligent mobile robot, which is driven by 2 D. C. motors, for clash avoidance in a way of direction toward an odour source. Throughout the experimental trails, it is confirmed that the intelligent mobile robot is capable of not only the odour recognition using artificial neural network algorithm, but also the tracking odour source using the step-by-step approach method. The preliminary results are promising that intelligent mobile robot, which has been developed, is applicable to service robot system for environmental monitoring, localization of odour source, odour tracking of hazardous areas etc.

• Journal of Institute of Control, Robotics and Systems
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• v.10 no.9
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• pp.809-815
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• 2004

Researches on mobile robots have been mainly focused on the autonomous navigation and a lot of interesting results have been published so far. Most of applications are, however, fancy, unpractical, and very expensive to be used for 'UN-expensive' purpose. Well-known soccer robot may be an example of unpractical application. Un-autonomous mobile robot has, however, potential for a lot of practical applications. Especially, tele-operation of the un-autonomous mobile robot may the central issue of research. Major research topics for the tele-operated un-autonomous mobile robot include development of a force reflecting joystick for tele-operation and development of a sophisticated algorithm for smooth tele-operation. A new concept named fuzzy command smoothing algorithm is proposed in this paper in order to provide smooth motion to a tele-operated mobile robot. It gives smooth motion command to the mobile robot from possibly abrupt quick turn motion command of the joystick using fuzzy logic. Simulation results verify the usefulness of the proposed algorithm.

• Journal of Institute of Control, Robotics and Systems
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• v.9 no.10
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• pp.798-807
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• 2003

We propose a blind mobile robot force control algorithm that uses force information as a guidance toward to the goal position. Based on the mobile robot dynamics, the control law is formed from explicit force errors. Simulation studies are conducted based on the kinematics and the dynamics of the mobile robot. Simulation results show that good force tracking can be achieved. In order to confirm simulation results, experiments are performed. The robot is commanded to follow unknown environment with maintaining a certain desired force. Experimental results show that the blind mobile robot successfully maintains contact with a regulated desired force and arrives at the goal position.