• Journal of Ocean Engineering and Technology
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• v.38 no.3
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• pp.115-123
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• 2024

USBL systems are essential for providing accurate positions of autonomous underwater vehicles (AUVs). On the other hand, the accuracy can be degraded by outliers because of the environmental conditions. A failure to address these outliers can significantly impact the reliability of underwater localization and navigation systems. This paper proposes a novel outlier rejection algorithm for AUV localization using Voronoi diagrams and query point calculation. The Voronoi diagram divides data space into Voronoi cells that center on ultra-short baseline (USBL) data, and the calculated query point determines if the corresponding USBL data is an inlier. This study conducted experiments acquiring GPS and USBL data simultaneously and optimized the algorithm empirically based on the acquired data. In addition, the proposed method was applied to a sensor fusion algorithm to verify its effectiveness, resulting in improved pose estimations. The proposed method can be applied to various sensor fusion algorithms as a preprocess and could be used for outlier rejection for other 2D-based location sensors.

• Journal of the Korean Data and Information Science Society
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• v.22 no.6
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• pp.1029-1040
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• 2011

In this paper we propose an intelligent navigation algorithm for real world problem which can build a map without localization. Proposed algorithm operates online and furthermore does not require many memories for applying real world problem. After applying proposed algorithm to toy and huge data set, it does not require to calculate a whole eigenspace and need less memory compared to existing algorithm. Thus we can obtain that proposed algorithm is suitable for real world mobile navigation algorithm.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.6A
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• pp.481-487
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• 2005

In order to increase the autonomous navigation capability of a mobile robot, it is very crucial to develop a method for recognizing a priori known environmental characteristics. This paper proposes an ultrasonic sensor based real-time method for recognizing a priori known indoor environmental characteristics like a wall and corner. The ultrasonic sensor consists of an ultrasonic transmitter and two ultrasonic receivers placed symmetrically about the transmitter. Unlike previous methods the information obtained from the sensor is processed in real-time by extended Kalman filter to be able to correct the position and orientation of robot with respect to known environmental characteristics.

• The Journal of Korea Robotics Society
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• v.12 no.4
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• pp.385-394
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• 2017

Side scanning sonar (SSS) provides valuable information for robot navigation. However using the side scanning sonar images in the navigation was not fully studied. In this paper, we use range data, and side scanning sonar images from UnderWater Simulator (UWSim) and propose measurement models in a feature based simultaneous localization and mapping (SLAM) framework. The range data is obtained by echosounder and sidescanning sonar images from side scan sonar module for UWSim. For the feature, we used the A-KAZE feature for the SSS image matching and adjusting the relative robot pose by SSS bundle adjustment (BA) with Ceres solver. We use BA for the loop closure constraint of pose-graph SLAM. We used the Incremental Smoothing and Mapping (iSAM) to optimize the graph. The optimized trajectory was compared against the dead reckoning (DR).

• Journal of Positioning, Navigation, and Timing
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• v.6 no.3
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• pp.105-116
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• 2017

Several wireless localization algorithms are evaluated for the IR-UWB-based indoor location with the assumption that the ranging measurements contain the channelwise Non-Calibration Error (NCE). The localization algorithms can be divided into the Model-free Localization (MfL) methods and Model-based Kalman Filtering (MbKF). The algorithms covered in this paper include Iterative Least Squares (ILS), Direct Solution (DS), Difference of Squared Ranging Measurements (DSRM), and ILS-Common (ILS-C) methods for the MfL methods, and Extended Kalman Filter (EKF), EKF-Each Channel (EKF-EC), EKF-C, Cubature Kalman Filter (CKF), and CKF-C for the MbKF. Experimental results show that the DSRM method has better accuracy than the other MfL methods. Also, it demands smallest computation time. On the other hand, the EKF-C and CKF-C require some more computation time than the DSRM method. The accuracy of the EKF-C and CKF-C is, however, best among the 9 methods. When comparing the EKF-C and CKF-C, the CKF-C can be easily used. Finally, it is concluded that the CKF-C can be widely used because of its ease of use as well as it accuracy.

• Journal of the Korean Society for Precision Engineering
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• v.26 no.8
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• pp.62-71
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• 2009

In mobile robotics, ultrasonic sensors became one of the most popular devices for collision avoidance and navigation primarily due to data robustness, the easy availability of low-cost systems, their compact size, simple circuits, and their ease in interfacing with computers. However, ultrasonic sonic sensors are subject to noise which results in inaccuracy of mapping and localization of the robot. This paper introduces a new approach to enhance environmental maps based on ultrasonic range data using linear interpolation and Newton interpolation. The simulation and experimental results show that the proposed method improves of the accuracy of the map through better distance estimation between the mobile robot and obstacles.

• Proceedings of the KIEE Conference
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• 2002.11c
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• pp.154-158
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• 2002

This paper describes a path tracking method for vision-based and autonomous mobile robot in a corridor. At first, we extract the ceiling-lamp of the corridor through simple preprocessing (gray, thresholding, labeling, etc.) for robot position and orientation. Then, we design the controller for path-tracking. Simulations conducted, and acceptable vehicle localization results were obtained to prove the feasibility of the proposed approach.

• Proceedings of the KIEE Conference
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• 2002.11c
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• pp.130-133
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• 2002

In this paper we suggest Inertial navigation system(INS) for the guidance robot for the visually impaired. we use 3 gyroscopes and 3 accelerometers and calculate using pentium III computer, we can acquire altitude and position of the guidance robot using this system.

• Journal of Institute of Control, Robotics and Systems
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• v.15 no.5
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• pp.480-487
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• 2009

Autonomous Lane detection with vision is a difficult problem because of various road conditions, such as shadowy road surface, various light conditions, and the signs on the road. In this paper we propose a robust lane detection algorithm to overcome shadowy road problem using a statistical method. The algorithm is applied to the vision-based mobile robot system and the robot followed the lane with the lane following controller. In parallel with the lane following controller, the global position of the robot is estimated by the developed localization method to specify the locations where the lane is discontinued. The results of experiments, done in the region where the GPS measurement is unreliable, show good performance to detect and to follow the lane in complex conditions with shades, water marks, and so on.

• The Journal of Korea Robotics Society
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• v.2 no.4
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• pp.334-340
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• 2007

This paper introduces a prototype smart home environment that is built in the research building to demonstrate the feasibility of a robot-assisted future home environment. Localization, navigation, object recognition and handling are core functionalities that an intelligent service robot should provide. A huge amount of research effort has been made to make the service robot perform these functions with its own sensors, actuators and a knowledge base. With all complicated configuration of sensors, actuators and a database, the robot could only perform the given tasks in a predefined environment or show the limited capabilities in a natural environment. We started a smart home environment for service robots for simple service robots to provide reliable services by communicating with the environment through the wireless sensor networks. In this paper, we introduce various types of smart devices that are developed for assisting the robot in the environment by providing sensor and actuator capabilities. In addition, we present how the devices are integrated to constitute the smart home environment for service robots.