• 조명전기설비학회논문지
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• 제20권9호
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• pp.45-53
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• 2006

This paper proposes a method for an effective intelligent route decision for automatic moving robots(AMR) using a 2D spatial map of a stereo camera system. In this method, information about depth and disparity map are detected in the inputting images of a parallel stereo camera. The distance between the automatic moving robot and the obstacle is detected, and a 2D spatial map is obtained from the location coordinates. Then the relative distances between the obstacle and other objects are deduced. The robot move automatically by effective and intelligent route decision using the obtained 2D spatial map. From experiments on robot driving with 240 frames of stereo images, it was found that the error ratio of the calculated distance to the measured distance between objects was very low, 1.52[%] on average.

• 한국경영과학회:학술대회논문집
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• 대한산업공학회/한국경영과학회 1996년도 춘계공동학술대회논문집; 공군사관학교, 청주; 26-27 Apr. 1996
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• pp.244-248
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• 1996

Nowadays, most shop floors using industrial robots have many problems such as constructing robot workcell, generating robot arm moving trajectory, etc.. In the case of programming robot-arms for a specific task, shop operator commonly use the teach pendant to record the target position and determine the moving trajectory. However, such a teaching process may result in an inefficient trajectory in the sense of moving distance and joint angle fluctuation. Moreover, shop operators who have little knowledge about robot programming process need a lot of learning time and cost. The purpose of this paper is to propose a user friendly robot programming method to program robot-arms easily and efficiently for shop operator so that the programming time is reduced and a short and stable trajectory is obtained.

• 한국정밀공학회지
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• 제17권8호
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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.

• 대한임베디드공학회논문지
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• 제14권3호
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• pp.151-156
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• 2019

According to recent advances in technology, major robot technologies that have been developed and commercialized for industrial use are being applied to various fields in our everyday life such as guide robots and cleaning robots. Among them, the navigation based on the self localization has become an essential element technology of the robot. In the case of indoor environment, many high-priced sensors are used, which makes it difficult to activate the robot industry. In this paper, we propose a robotic platform and a moving algorithm that can travel by using Dijkstra algorithm. The proposed system can find a short route to the destination with its own position. Also, its performance is discussed through the experimentation of an actual robot.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2004년도 ICCAS
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• pp.678-681
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• 2004

In this paper, efficient tracking of a moving object using optimal representative blocks is implemented by a mobile robot with a pan-tilt camera. The key idea comes from the fact that when the image size of moving object is shrunk in an image frame according to the distance between the camera of mobile robot and the moving object, the tracking performance of a moving object can be improved by changing the size of representative blocks according to the object image size. Motion estimation using Edge Detection(ED) and Block-Matching Algorithm(BMA) is often used in the case of moving object tracking by vision sensors. However these methods often miss the real-time vision data since these schemes suffer from the heavy computational load. In this paper, the optimal representative block that can reduce a lot of data to be computed, is defined and optimized by changing the size of representative block according to the size of object in the image frame to improve the tracking performance. The proposed algorithm is verified experimentally by using a two degree-of-freedom active camera mounted on a mobile robot.

• Transactions on Control, Automation and Systems Engineering
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• 제4권1호
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• pp.56-61
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• 2002

In this paper we describe an approach to coordinating the motion of a human with a mobile robot moving in a populated, continuously changing. natural environment. Our test application is a wheelchair accompanying a person through the concourse of a railway station moving side by side with the person. Our approach is based on a method for motion planning amongst moving obstacles known as Velocity Obstacle approach. We extend this method by a method for tracking a virtual target which allows us to vary the robot's heading and velocity with the locomotion of the accompanied person and the state of the surrounding environment.

• 제어로봇시스템학회논문지
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• 제7권9호
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• pp.741-748
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• 2001

In this paper, we propose a method of tracking and capturing a moving object by a mobile robot. The position of the moving object is acquired from the relation through color-based image information from a 2-DOF active camera mounted on the mobile robot. The direction and rotational angular velocity of the moving object are estimated using a state estimator. A Kalman fiber is used as the state estimator for taking characteristics of robustness against noises and uncertainties included in the input data. After estimating the trajectory of the moving object, we decide on the optimal trajectory and plan the motion of the mobile robot to capture the target object within the shortest distance and time. The effectiveness of the proposed method is demonstrated by the simulations and experiments.

• International Journal of Control, Automation, and Systems
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• 제3권3호
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• pp.444-452
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• 2005

A new scheme for a mobile robot to track and capture a moving object using camera images is proposed. The moving object is assumed to be a point-object and is projected onto an image plane to form a geometrical constraint equation that provides the position data of the object based on the kinematics of the active camera. Uncertainties in position estimation caused by the point-object assumption are compensated for using the Kalman filter. To generate the shortest time path to capture the moving object, the linear and angular velocities are estimated and utilized. In this paper, the experimental results of the tracking and capturing of a target object with the mobile robot are presented.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2011년도 제42회 하계학술대회
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• pp.1916-1917
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• 2011

A development of a new moving obstacle avoidance algorithm using a delay-time Compensation for a network-based autonomous mobile robot is proposed in this paper. The moving obstacle avoidance algorithm is based on a Kalman filter through moving obstacle estimation and a Bezier curve for path generation. And, the network-based mobile robot, that is a unified system composed of distributed environmental sensors, mobile actuators, and controller, is compensated by a network delay compensation algorithm for degradation performance by network delay. The network delay compensation method by a sensor fusion using the Kalman filter is proposed for the localization of the robot to compensate both the delay of readings of an odometry and the delay of reading of environmental sensors. Through some simulation tests, the performance enhancement of the proposed algorithm in the viewpoint of efficient path generation and accurate goal point is shown here.

• 제어로봇시스템학회논문지
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• 제5권8호
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• pp.990-994
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• 1999

This paper proposes a new fuzzy-neural algorithm for navigation of a mobile robot with stationary and moving obstacles environment. The proposed algorithm uses fuzzy algorithm for its speed control and neuralnetwork for effective collision avoidance. Some computer simulation results for a mobile robot equipped with ultrasonic range sensors show that the suggested navigation algorithm is very effective to escape in stationary and moving obstacles environment.