• Title/Summary/Keyword: Mobile robot localization

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Localization of Mobile Robot using Active Landmark (능동형 인공표지를 이용한 이동로봇의 위치 인식)

  • Lee, Jae-Kyung;Park, Young-Hwan
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.9 no.1
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    • pp.64-69
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    • 2008
  • In order that a mobile robot can perform tasks in unknown environment localization of a mobile robot is essential task. In this paper, a new localization method for a mobile robot using an active landmark is proposed, which is very simple to implement. The landmark has a LED which can be controlled by a mobile robot via wireless communication. CCD camera gets two images of the landmark, one of which is with LED off and the other is with LED on. Because the landmark can be detected by using the difference image of the two images, detection time can be minimized. By using the characteristic points of the landmark, localization can be performed simply. A series of experiments are performed to evaluate the proposed method and the experimental results show that the proposed method can be applicable to the localization of a mobile robot.

Passive RFID Based Mobile Robot Localization and Effective Floor Tag Arrangement (수동 RFID 기반 이동로봇 위치 추정 및 효율적 노면 태그 배치)

  • Kim, Sung-Bok;Lee, Sang-Hyup
    • Journal of Institute of Control, Robotics and Systems
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    • v.14 no.12
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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.

Monte Carlo Localization for Mobile Robots Under REID Tag Infrastructures (RFID 태그에 기반한 이동 로봇의 몬테카를로 위치추정)

  • Seo Dae-Sung;Lee Ho-Gil;Kim Hong-Suck;Yang Gwang-Woong;Won Dae-Hee
    • Journal of Institute of Control, Robotics and Systems
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    • v.12 no.1
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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.

Localization of Mobile Robot Using Color Landmark mounted on Ceiling (천장 부착 컬러 표식을 이용한 이동로봇의 자기위치추정)

  • Oh, Jong-Kyu;Lee, Chan-Ho
    • Proceedings of the KIEE Conference
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    • 2001.11c
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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.

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An Efficient Localization of Mobile Robot in RFID Sensor Space (RFID 센서 공간에서의 모바일 로봇의 효율적인 위치 인식)

  • Choi, Byoung-Suk;Lee, Jang-Myung
    • Journal of Institute of Control, Robotics and Systems
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    • v.12 no.1
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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.

Absolute Positioning System for Mobile Robot Navigation in an Indoor Environment (ICCAS 2004)

  • Yun, Jae-Mu;Park, Jin-Woo;Choi, Ho-Seek;Lee, Jang-Myung
    • 제어로봇시스템학회:학술대회논문집
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    • 2004.08a
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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.

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A study on approach of localization problem using landmarks (Landmark를 이용한 localization 문제 접근에 관한 연구)

  • 김태우;이쾌희
    • 제어로봇시스템학회:학술대회논문집
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    • 1997.10a
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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.

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Self Localization of Mobile Robot Using Sonar Sensing and Map Building

  • Kim, Ji-Min;Lee, Ki-Seong;Jeong, Tae-Won
    • 제어로봇시스템학회:학술대회논문집
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    • 2004.08a
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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.

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Position Improvement of a Human-Following Mobile Robot Using Image Information of Walking Human (보행자의 영상정보를 이용한 인간추종 이동로봇의 위치 개선)

  • Jin Tae-Seok;Lee Dong-Heui;Lee Jang-Myung
    • 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.

Indoor Localization of a Mobile Robot Using External Sensor (외부 센서를 이용한 이동 로봇 실내 위치 추정)

  • Ko, Nak-Yong;Kim, Tae-Gyun
    • Journal of Institute of Control, Robotics and Systems
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    • v.16 no.5
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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.