• Journal of Institute of Control, Robotics and Systems
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• v.11 no.5
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• pp.429-434
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• 2005

In this paper, the maze navigation system using image recognition for autonomous mobile robot is proposed. The proposed maze navigation system searches the target by image recognition method based on ADALINE neural network. The infrared sensor system must travel all blocks to find target because it can recognize only one block information each time. But the proposed maze navigation system can reduce the number of traveling blocks because of the ability of sensing several blocks at once. Especially, due to the simplicity of the algorithm, the proposed method could be easily implemented to the system which has low capacity processor.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.1
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• pp.114-120
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• 2017

The work present in this paper deals with a navigation problem for multiple mobile robots in unknown indoor environments. The environments are completely unknown to the robots; thus, proximity sensors installed on the robots' bodies must be used to detect information about the surroundings. The environments simulated in this work are dynamic ones which contain not only static but also moving obstacles. In order to guide the robot to move along a collision-free path and reach the goal, this paper presented a navigation method based on fuzzy approach. Then genetic algorithms were applied to optimize the membership functions and rules of the fuzzy controller. The simulation results verified that the proposed method effectively addresses the mobile robot navigation problem.

• Journal of information and communication convergence engineering
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• v.11 no.1
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• pp.24-29
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• 2013

In this paper, we propose a fuzzy inference model for a navigation algorithm for a mobile robot that intelligently searches goal location in unknown dynamic environments. Our model uses sensor fusion based on situational commands using an ultrasonic sensor. Instead of using the "physical sensor fusion" method, which generates the trajectory of a robot based upon the environment model and sensory data, a "command fusion" method is used to govern the robot motions. The navigation strategy is based on a combination of fuzzy rules tuned for both goal-approach and obstacle-avoidance based on a hierarchical behavior-based control architecture. To identify the environments, a command fusion technique is introduced where the sensory data of the ultrasonic sensors and a vision sensor are fused into the identification process. The result of experiment has shown that highlights interesting aspects of the goal seeking, obstacle avoiding, decision making process that arise from navigation interaction.

• ETRI Journal
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• v.43 no.4
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• pp.617-629
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• 2021

Although the actual visual simultaneous localization and mapping (SLAM) algorithms provide highly accurate tracking and mapping, most algorithms are too heavy to run live on embedded devices. In addition, the maps they produce are often unsuitable for path planning. To mitigate these issues, we propose a completely closed-loop online dense RGB-D SLAM algorithm targeting autonomous indoor mobile robot navigation tasks. The proposed algorithm runs live on an NVIDIA Jetson board embedded on a two-wheel differential-drive robot. It exhibits lightweight three-dimensional mapping, room-scale consistency, accurate pose tracking, and robustness to moving objects. Further, we introduce a navigation strategy based on the proposed algorithm. Experimental results demonstrate the robustness of the proposed SLAM algorithm, its computational efficiency, and its benefits for on-the-fly navigation while mapping.

• Spatial Information Research
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• v.20 no.5
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• pp.67-76
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• 2012

Recently the mobile DBMS (Database Management System) is popular to store and manage large data in a mobile device. Especially, the research and development about mobile storage structure and querying method for navigation map data in a mobile device have been performed. The performance of the mobile DBMS in which random data accesses are most queries if the NAND flash memory is used as storage media of the DBMS is degraded. The reason is that the performance of flash memory is good in writing sequentially but bad in writing randomly as the features of the NAND flash memory. So, new storage structure and querying policies of the mobile DBMS are needed in the mobile DBMS in which a flash memory is used as storage media. In this paper, we have studied the policy of the database page management to enhance the performance of the frequent random update and applied this policy to the navigation-specialized mobile DBMS which supports incremental map update. And also we have evaluated the performance of this policy by experiments.

• IEMEK Journal of Embedded Systems and Applications
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• v.10 no.6
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• pp.373-379
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• 2015

A hybrid navigation system is implemented to apply for a mobile robot. The hybrid navigation system consists of an inertial navigation system and a global positioning system. The inertial navigation system quickly calculates the position and the attitude of the robot by integrating directional accelerations, angular speed, and heading angle from a strap-down inertial measurement unit, but the results are available for a short time since it tends to diverge quickly. Global positioning system delivers position, heading angle, and traveling speed stably, but it has large deviation with slow update. Therefore, a hybrid navigation system uses the result from an inertial navigation system and corrects the result with the help of the global positioning system where an indirect feedback Kalman filter is used. We implement and confirm the performance of the hybrid navigation system through driving a car attaching it.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.10
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• pp.1738-1745
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• 2016

In this paper, we present localization and autonomous navigation method using GPU(Graphics Processing Unit)-based SIFT(Scale-Invariant Feature Transform) algorithm and virtual force method for mobile robots. To do this, at first, we propose the localization method to recognize the landmark using the GPU-based SIFT algorithm and to update the position using extended Kalman filter. And then, we propose the A-star algorithm for path planning and the virtual force method for autonomous navigation of the mobile robot. Finally, we demonstrate the effectiveness and applicability of the proposed method through some experiments using the mobile robot with OPRoS(Open Platform for Robotic Services).

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1994.04a
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• pp.42-48
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• 1994

This paper presents the navigation method for a mobile robot which uses a single camera and fluorescent lamp as a guide mark, projected on a convex mirror. The current position and heading direction of the mobile robot are obtained from the image of the guide mark. While the mobile robot travels to a goal position, the current position and heading direction of the mobile robot are updated continuously and the desired path and actual moving path are displayed on the monitor screen in real time. This proposed method eliminates the need to rotate the camera to track the guide mark, since a panoramic view of the surrounding area is available from the convex mirror, and natural guide marks such as usual florescent lamp on the ceiling or door frame can be used for navigation.

• Journal of the Korean Society of Industry Convergence
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• v.21 no.2
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• pp.95-101
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• 2018

This paper presents a collision free mobile robot navigation based on the fuzzy inference fusion model in unkonown environments using multi-ultrasonic sensor. Six ultrasonic sensors are used for the collision avoidance approach where CCD camera sensors is used for the trajectory following approach. The fuzzy system is composed of three inputs which are the six distance sensors and the camera, two outputs which are the left and right velocities of the mobile robot's wheels, and three cost functions for the robot's movement, direction, obstacle avoidance, and rotation. For the evaluation of the proposed algorithm, we performed real experiments with mobile robot with ultrasonic sensors. The results show that the proposed algorithm is apt to identify obstacles in unknown environments to guide the robot to the goal location safely.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.20 no.2
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• pp.133-138
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• 2011

RFID system can be used to improve object recognition, map building and localization for robot area. A novel method of indoor navigation system for a mobile robot is proposed using RFID technology. The mobile robot With a RFID reader and antenna is able to find what obstacles are located where in circumstance and can build the map similar to indoor circumstance by combining RFID information and distance data obtained from sensors. Using the map obtained, the mobile robot can avoid obstacles and finally reach the desired goal by $A^*$ algorithm. 3D map which has the advantage of robot navigation and manipulation is able to be built using z dimension of products. The proposed robot navigation system is proved to apply for SLAM and path planning in unknown circumstance through numerous experiments.