• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.237-240
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• 1997

The design of underwater inspection robot system is presented. This robot system is designed for wall inspection in the nuclear plant facility. This paper describes the major components of the robot and its structures. This robot system is consisted of three parts : mechanical electrical and sensing pail. The main problem of designing mechanical part is to select the mechanism of driving. In this system the propeller driving mechanism is selected which can be move the robot continuously. For reducing the size of robot, we designed the CPU and motor controller board. The sensor system is consisted of two parts. One is environment monitoring part and the other is robot localization system.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2000.11a
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• pp.666-669
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• 2000

Localization is the process of aligning the robot's local coordinates with the global coordinates of a map. A mobile robot's location is basically computed by a dead reckoning scheme, but this position information becomes increasingly inaccurate during navigation due to odometry errors. In this paper, the method of building a map of a robot's environment using ultrasonic sensor data and the occupancy grid map scheme is briefly presented. Then, the search and matching algorithms to compensate for the odometry error by comparing the local map with the reference map are proposed and verified by experiments. It is shown that the compensated error is not accumulated and exists within the limited range.

• The Journal of the Korea institute of electronic communication sciences
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• v.8 no.3
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• pp.421-432
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• 2013

This paper describes implementation of functions for mobile robot localization, which is one of the vital technologies for autonomous navigation of a mobile robot. There are several function libraries for mobile robot navigation. Some of them have limited applicability for practical use since they can be used only for simulation. Our research focuses on development of functions which can be used for localization of indoor robots. The functions implement deadreckoning and motion model of mobile robots, measurement model of range sensors, and frequently used calculations on angular directions. The functions encompass various types of robots and sensors. Also, various types of uncertainties in robot motion and sensor measurements are implemented so that the user can select proper ones for their use. The functions are tested and verified through simulation and experiments.

• Proceedings of the KIEE Conference
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• 2011.07a
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• pp.1934-1935
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• 2011

In order for a service robot to perform several tasks, basically autonomous navigation technique such as localization, mapping, and path planning is required. The localization (estimation robot's pose) is fundamental ability for service robot to navigate autonomously. In this paper, we propose a new system for point pattern matching based visual global localization using spot lightings in ceiling. The proposed algorithm us suitable for system that demands high accuracy and fast update rate such a guide robot in the exhibition. A single camera looking upward direction (called ceiling vision system) is mounted on the head of the mobile robot and image features such as lightings are detected and tracked through the image sequence. For detecting more spot lightings, we choose wide FOV lens, and inevitably there is serious image distortion. But by applying correction calculation only for the position of spot lightings not whole image pixels, we can decrease the processing time. And then using point pattern matching and least square estimation, finally we can get the precise position and orientation of the mobile robot. Experimental results demonstrate the accuracy and update rate of the proposed algorithm in real environments.

• Journal of the Korean Society for Precision Engineering
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• v.16 no.1 s.94
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• pp.253-264
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• 1999

Most autonomous mobile robots view only things in front of them, and as a result, they may collide with objects moving from the side or behind. To overcome this problem. an Active Omni-directional Range Sensor System has been built that can obtain an omni-directional range data through the use of a laser conic plane and a conic mirror. Also, mobile robot has to know its current location and heading angle by itself as accurately as possible to successfully navigate in real environments. To achieve this capability, we propose a self-localization algorithm of a mobile robot using an active omni-directional range sensor in an unknown environment. The proposed algorithm estimates the current position and head angle of a mobile robot by a registration of the range data obtained at two positions, current and previous. To show the effectiveness of the proposed algorithm, a series of simulations was conducted and the results show that the proposed algorithm is very efficient, and can be utilized for self-localization of a mobile robot in an unknown environment.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.9
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• pp.903-909
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• 2007

Mobile Robots are increasingly being used to perform tasks in unknown environment. The potential of robots to undertake such tasks lies in their ability to intelligently and efficiently search in an environment. To achieve autonomous mobile robot navigation, efficient path planner and accurate localization technique are the fundamental issues that should be addressed. This paper presents mobile robot localization using IRID(InfraRed IDentification) as artificial landmarks. IRID has highly deterministic characteristics, different from RFID. By putting several IRID emitters on the ceiling, the floor is divided into many different sectors and each sector is set to have a unique identification. Dead-reckoning provides the estimated robot configuration but the error becomes accumulated as the robot travels. IRID information tells the sector the robot is in, but the size of the uncertainty is too large if only the IRID information is used. This paper presents an algorithm which combines both the encoder and the IRID information so that the size of the uncertainty becomes smaller. It also introduces a framework which can be used with other types of the artificial landmarks. The characteristics of the developed IRID and the proposed algorithm are verified from the simulation results and experiments.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.9
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• pp.813-821
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• 2013

In this paper, we present the development of P-SURO II hybrid AUV (Autonomous Underwater Vehicle) which can be operated in both of AUV and ROV (Remotely Operated Vehicle) modes. In its AUV mode, the vehicle is supposed to carry out some of underwater missions which are difficult to be achieved in ROV mode due to the tether cable. To accomplish its missions such as inspection and maintenance of complex underwater structures in AUV mode, the vehicle is required to have high level of autonomy including environmental recognition, obstacle avoidance, autonomous navigation, and so on. In addition to its systematic development issues, some of algorithmic issues are also discussed in this paper. Various experimental studies are also presented to demonstrate these developed autonomy algorithms.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.4
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• pp.817-823
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• 2009

This paper proposes a robust method for mapping of a caterpillar-type mobile robot which inherently has uncertainty in its modeling by compensating for the estimated pose error of the robot. In general, a caterpillar type robot is difficult to model, which results in inaccuracy in Simultaneous Localization And Mapping(SLAM). To enhance the robustness of the SLAM for a caterpillar-type mobile robot, we factorize the SLAM posterior, where we used particle filter to estimate the position of the robot and Extended Kalman Filter(EKF) to map the environment. The simulation results show the effectiveness and robustness of the proposed method for mapping.

• IEMEK Journal of Embedded Systems and Applications
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• v.14 no.3
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• pp.151-156
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• 2019

According to recent advances in technology, major robot technologies that have been developed and commercialized for industrial use are being applied to various fields in our everyday life such as guide robots and cleaning robots. Among them, the navigation based on the self localization has become an essential element technology of the robot. In the case of indoor environment, many high-priced sensors are used, which makes it difficult to activate the robot industry. In this paper, we propose a robotic platform and a moving algorithm that can travel by using Dijkstra algorithm. The proposed system can find a short route to the destination with its own position. Also, its performance is discussed through the experimentation of an actual robot.

• Journal of KIISE:Software and Applications
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• v.37 no.8
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• pp.641-646
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• 2010

This paper presents algorithms for real-time navigation of a humanoid robot with a stereo vision but no other sensors. Using the algorithms, a robot can recognize its 3D environment by retrieving SIFT features from images, estimate its position through the Kalman filter, and plan its path to reach a destination avoiding obstacles. Our approach focuses on estimating the robot’s central walking path trajectory rather than its actual walking motion by using an approximate model. This strategy makes it possible to apply mobile robot localization approaches to humanoid robot localization. Simple collision free path planning and motion control enable the autonomous robot navigation. Experimental results demonstrate the feasibility of our approach.