• 한국산학기술학회논문지
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• 제9권1호
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• pp.64-69
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• 2008

이동로봇이 임의의 작업공간에서 임무를 수행하기 위해서는 주변 환경에 대한 위치 인식 능력이 있어야 한다. 본 논문에서는 새로운 능동형 인공표지를 이용하여 이동로봇의 위치를 인식할 수 있는 방법을 제안한다. 능동형 인공표지에는 이동로봇에서 무선통신으로 제어가 가능한 LED가 부착되어 있는데, 제안한 방법은 CCD 카메라로 인공표지의 LED가 점등 및 소등된 두 영상의 차영상을 이용하여 인공표지 여부를 판별하기 때문에 주변 환경의 복잡도에 관계없이 인식시간을 최소화할 수 있으며 인공표지의 특징점 정보를 이용하여 간단하게 위치를 인식할 수 있다. 제안한 방법의 성능을 평가하기 위하여 실험을 하였으며 실험 결과는 제안한 방법이 이동로봇의 위치 인식에 적용될 수 있음을 보였다.

• 제어로봇시스템학회논문지
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• 제14권12호
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• pp.1294-1301
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• 2008

Under passive RFID environment, this paper presents a new localization of a mobile robot traversing over the floor covered with tags, which is superior to existing methods in terms of estimation performance and cost effectiveness. Basically, it is assumed that a mobile robot is traveling along a series of straight line segments, each segment at a certain constant velocity, and that the number of tags sensed by a mobile robot at each sampling instant is at most one. First, for a given line segment with known starting point, the velocity and position of a mobile robot is estimated using the spatial and temporal information acquired from the traversed tag. Some discussions are made on the validity of the basic assumptions and the localization for the initial segment with unknown starting point. Second, for a given tag distribution density, the optimal tag arrangement is considered to reduce the position estimation error as well as to make easy the tag attachment on the floor. After reviewing typical tag arrangements, the pseudorandom tag arrangement is devised inspired from the Sudoku puzzle, a number placement puzzle. Third, through experiments using our passive RFID localization system, the validity and performance of the mobile robot localization proposed in this paper is demonstrated.

• 제어로봇시스템학회논문지
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• 제12궈1호
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• pp.47-53
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• 2006

Localization is a essential technology for mobile robot to work well. Until now expensive sensors such as laser sensors have been used for mobile robot localization. We suggest RFID tag based localization system. RFID tag devices, antennas and tags are cheap and will be cheaper in the future. The RFID tag system is one of the most important elements in the ubiquitous system and RFID tag will be attached to all sorts of goods. Then, we can use this tags for mobile robot localization without additional costs. So, in this paper, the smart floor using passive RFID tags is proposed and, passive RFID tags are mainly used for identifying mobile robot's location and pose in the smart floor. We discuss a number of challenges related to this approach, such as tag distribution (density and structure), typing and clustering. When a mobile robot localizes in this smart floor, the localization error mainly results from the sensing range of the RFID reader, because the reader just ran know whether a tag is in the sensing range of the sensor. So, in this paper, we suggest two algorithms to reduce this error. We apply the particle filter based Monte Carlo localization algorithm to reduce the localization error. And with simulations and experiments, we show the possibility of our particle filter based Monte Carlo localization in the RFID tag based localization system.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2001년도 합동 추계학술대회 논문집 정보 및 제어부문
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• pp.91-94
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• 2001

In this paper, we proposed localization method of mobile robot using color landmark mounted on ceiling. This work is composed 2 parts : landmark recognition part which finds the position of multiple landmarks in image and identifies them and absolute position estimation part which estimates the location and orientation of mobile robot in indoor environment. In landmark recognition part, mobile robot detects artificial color landmarks using simple histogram intersection method in rg color space which is insensitive to the change of illumination. Then absolute position estimation part calculates relative position of the mobile robot to the detected landmarks. For the verification of proposed algorithm, ceiling-orientated camera was installed on a mobile robot and performance of localization was examined by designed artificial color landmarks. As the result of test, mobile robot could achieve the reliable landmark detection and accurately estimate the position of mobile robot in indoor environment.

• 제어로봇시스템학회논문지
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• 제12궈1호
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• pp.15-22
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• 2006

This paper presents an efficient localization scheme for an indoor mobile robot using RFID tags on the floor. The mobile robot carries an RFID reader at the bottom, which reads the RFID tags on the floor to localize the mobile robot. Each RFID tar on the floor stores its own absolute position which is used to calculate the position and velocity of the mobile robot. Locating the RFID tags on the floor, which constructs an intelligent sensor space, may require several factors to be considered: economics feasibility and accuracy. In this paper, the optimal allocation scheme of the RFID tags on the floor to satisfy the accuracy constraint has been proposed and verified by the experiments. Based on the RFID reading, the mobile robot navigation has been successfully demonstrated to avoid obstacles and to reach the goal within a pre-specified time.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2004년도 ICCAS
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• pp.1448-1451
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• 2004

Position estimation is one of the most important functions for the mobile robot navigating in the unstructured environment. Most of previous localization schemes estimate current position and pose of mobile robot by applying various localization algorithms with the information obtained from sensors which are set on the mobile robot, or by recognizing an artificial landmark attached on the wall, or objects of the environment as natural landmark in the indoor environment. Several drawbacks about them have been brought up. To compensate the drawbacks, a new localization method that estimates the absolute position of the mobile robot by using a fixed camera on the ceiling in the corridor is proposed. And also, it can improve the success rate for position estimation using the proposed method, which calculates the real size of an object. This scheme is not a relative localization, which decreases the position error through algorithms with noisy sensor data, but a kind of absolute localization. The effectiveness of the proposed localization scheme is demonstrated through the experiments.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1997년도 한국자동제어학술회의논문집; 한국전력공사 서울연수원; 17-18 Oct. 1997
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• pp.44-47
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• 1997

Building a reliable mobile robot - one that can navigate without failures for long periods of time - requires that the uncertainty which results from control and sensing is bounded. This paper proposes a new mobile robot localization method using artificial landmarks. For a mobile robot localization, the proposed method uses a camera calibration(only extrinsic parameters). We use the FANUC arc mate to estimate the posture error, and the result shows that the position error is less than 1 cm and the orientation error less than 1 degrees.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2004년도 ICCAS
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• pp.1931-1935
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• 2004

A location estimate problem is critical issues for mobile robot. Because it is basic problem in practical use of the mobile robot which do what, or move where, or reach an aim. Already there are many technologies of robot localization (like GPS, vision, sonar sensor, etc) used on development. But the elevation of accurateness was brought the problem that must consider an increase of a hardware cost and addition electric power in each ways. There is the core in question to develop available and accurate sensing algorithm though it is economical. We used a ultrasonic sensor and was going to implement comparatively accurate localization though economical. Using a sensing data, we could make a grid map and estimate a position of a mobile robot. In this paper, to get a satisfactory answer about this problem using a ultrasonic sensor.

• 제어로봇시스템학회논문지
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• 제11권5호
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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.

• 제어로봇시스템학회논문지
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• 제16권5호
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• pp.420-427
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• 2010

This paper describes a localization method based on Monte Carlo Localization approach for a mobile robot. The method uses range data which are measured from ultrasound transmitting beacons whose locations are given a priori. The ultrasound receiver on-board a robot detects the range from the beacons. The method requires several beacons, theoretically over three. The method proposes a sensor model for the range sensing based on statistical analysis of the sensor output. The experiment uses commercialized beacons and detector which are used for trilateration localization. The performance of the proposed method is verified through real implementation. Especially, it is shown that the performance of the localization degrades as the sensor update rate decreases compared with the MCL algorithm update rate. Though the method requires exact location of the beacons, it doesn't require geometrical map information of the environment. Also, it is applicable to estimation of the location of both the beacons and robot simultaneously.