• The Journal of Korea Robotics Society
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• v.11 no.3
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• pp.127-132
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• 2016

For a practical mobile robot team such as carrying out a search and rescue mission in a disaster area, the localization have to be guaranteed even in an environment where the network infrastructure is destroyed or a global positioning system (GPS) is unavailable. The proposed architecture supports localizing robots seamlessly by finding their relative locations while moving from a global outdoor environment to a local indoor position. The proposed schemes use a cooperative positioning system (CPS) based on the two-way ranging (TWR) technique. In the proposed TWR-based CPS, each non-localized mobile robot act as tag, and finds its position using bilateral range measurements of all localized mobile robots. The localized mobile robots act as anchors, and support the localization of mobile robots in the GPS-shadow region such as an indoor environment. As a tag localizes its position with anchors, the position error of the anchor propagates to the tag, and the position error of the tag accumulates the position errors of the anchor. To minimize the effect of error propagation, this paper suggests the new scheme of full-mesh based CPS for improving the position accuracy. The proposed schemes assuring localization were validated through experiment results.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.7
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• pp.658-663
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• 2012

An accurate outdoor localization method using line/arc features is suggested for mobile robots with LRFs (Laser Range Finders) and odometry. Localization is a key process for outdoor mobile robots which are used for autonomous navigation, exploration and so on. In this paper, an accurate pose correction algorithm is proposed for mobile robots using LRFs, which use three feature types: line, circle, and arc. Using this method we can reduce the number of singular cases that robots couldn't find their pose. Finally we have got simulation results to validate the proposed algorithm.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2003.06a
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• pp.306-311
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• 2003

This paper presents a novel localization paradigm for mobile robots based on artificial and natural landmarks. A model-based object recognition method detects natural landmarks and conducts the global and topological localization. In addition, a metric localization method using artificial landmarks is fused to complement the deficiency of topology map and guide to action behavior. The recognition algorithm uses a modified local Zernike moments and a probabilistic voting method for the robust detection of objects in cluttered indoor environments. An artificial landmark is designed to have a three-dimensional multi-colored structure and the projection distortion of the structure encodes the distance and viewing direction of the robot. We demonstrate the feasibility of the proposed system through real world experiments using a mobile robot, KASIRI-III.

• IEMEK Journal of Embedded Systems and Applications
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• v.3 no.2
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• pp.109-118
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• 2008

We present a robust localization algorithm using particle filter for mobile robots in a dynamic environment. It is difficult to describe moving obstacles like people or other robots on the map and the environment is changed after mapping. A mobile robot cannot estimate its pose robustly with this incomplete map because sensor observations are corrupted by un-modeled obstacles. The proposed algorithms provide robustness in such a dynamic environment by suppressing the effect of corrupted sensor observations with a selective update or a sampling from non-corrupted window. A selective update method makes some particles keep track of the robot, not affected by the corrupted observation. In a sampling from non-corrupted window method, particles are always sampled from several particle sets which use only non-corrupted observation. The robustness of proposed algorithm is validated with experiments and simulations.

• Proceedings of the KIEE Conference
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• 2006.10c
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• pp.557-559
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• 2006

In this paper we analyze whether recent Radio Frequence Identification technology can be used to improve the localization of mobile robot and persons in their environment. In particular we study the problem of localizing RFID tags with a mobile platform that is equipped with a pair of RFID antennas. This system make use of power control because Tag with Reader distance measurement. We are accurately the low at former time than the environment. A distance measurement is rather correct. This system uses 900MHz Frequencies.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.42 no.2 s.302
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• pp.1-10
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• 2005

This paper presents a technique for localization of a mobile robot using a single ultrasonic sensor. The mobile robot is designed for operating in a well-structured environment that can be represented by planes, edges, corners and cylinders in the view of structural features. In the case of ultrasonic sensors, these features have the range information in the form of the arc of a circle that is generally named as RCD (Region of Constant Depth). Localization is the continual provision of a knowledge of position which is deduced from it's a priori position estimation. The environment of a robot is modeled into a two dimensional grid map. we defines a physically-based sonar sensor model and employs an extended Kalman filter to estimate position of the robot. The performance and simplicity of the approach is demonstrated with the results produced by sets of experiments using a mobile robot.

• The Journal of Korea Robotics Society
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• v.1 no.2
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• pp.117-124
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• 2006

In this paper, we develope the navigation system for patrol robots in indoor environment. The proposed system consists of PDA map modelling, a localization algorithm based on a global position sensor and an automatic charging station. For the practical use in security system, the PDA is used to build object map on the given indoor map. And the builded map is downloaded to the mobile robot and used in path planning. The global path planning is performed with a localization sensor and the downloaded map. As a main controller, we use PXA270 based hardware platform in which embedded linux 2.6 is developed. Data handling for various sensors and the localization algorithm are performed in the linux platform. Also, we implemented a local path planning algorithm for object avoidance with ultra sonar sensors. Finally, for the automatic charging, we use an infrared ray system and develop a docking algorithm. The navigation system is experimented with the two-wheeled mobile robot using North-Star localization system.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.831-833
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• 2004

In this paper, an obstacle avoidance algorithm is proposed for a network-based robot considering network delay by distribution. The proposed algorithm is based on the VFH(Vector Field Histogram) algorithm, and for the network-based robot system, in which it is assumed robot localization information is transmitted through network communication. In this paper, target vector for the VFH algorithm is estimated through the robot localization information and the measurement of its delay by distribution. The delay measurement is performed by time-stamp method. To synchronize all local clocks of the nodes distributed on the network, a global clock synchronization method is adopted. With the delay measurement, the robot localization estimation is performed by calculating the kinematics of the robot. The validation of the proposed algorithm is performed through the performance comparison of the obstacle avoidance between the proposed algorithm and the existing VFH algorithm on the network-based autonomous mobile robot.

• The Journal of Korea Robotics Society
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• v.9 no.2
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• pp.96-103
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• 2014

Global localization is one of the essential issues for mobile robot navigation. In this study, an indoor global localization method is proposed which uses a Kinect sensor and a monocular upward-looking camera. The proposed method generates an environment map which consists of a grid map, a ceiling feature map from the upward-looking camera, and a spatial feature map obtained from the Kinect sensor. The method selects robot pose candidates using the spatial feature map and updates sample poses by particle filter based on the grid map. Localization success is determined by calculating the matching error from the ceiling feature map. In various experiments, the proposed method achieved a position accuracy of 0.12m and a position update speed of 10.4s, which is robust enough for real-world applications.

• Proceedings of the KIEE Conference
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• 2007.04a
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• pp.352-354
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• 2007

This paper presents a method to estimate the position of a mobile robot by using a gyro sensor and accelerometer sensors on it. Together with contact sensors we propose a mapmaking algorithm for an indoor environment where the robot moves. The direction of robot can be estimated through a gyro sensor and the distance is founded out by accelerometers. Then one can presume the position of robot. Using the direction and distance values vector-based mapmaking job can be performed. Tactile sensors help the robot recognize the boundary limit value of indoor environment and decide outer wall line of the map.