• The Transactions of the Korean Institute of Electrical Engineers
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• v.41 no.9
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• pp.1071-1084
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• 1992

In this paper, the method for navigation and obstacle avoidance of the autonomous mobile robot is proposed. The proposed algorithms are based on the fuzzy inference system which is able to deal with imprecise and uncertain information. The self-tuning algorithm, which adopts the simplex method, modifies the parameters of membership functions of the input-output linguistic variables by changing the support of these fuzzy sets according to the integral of absolute error(IAE) of the system response. The wall-follwing navigation and obstacle avoidance of the mobile robot are based on range data measured from the internal sensors(encoder) and the outer sensors(sonar sensor). In addition, the algorithm for the obstacle detection proposed in this paper is based on the expert's experience. Finally, the effectiveness of navigation and obstacle avoidance algorithm is demonstrated through simulation and experiment.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.9
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• pp.875-882
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• 2007

In order for a vehicle to follow a predetermined trajectory accurately, its position must be estimated accurately and reliably. In this thesis, we propose trajectory tracking control methods for unmanned vehicle and a positioning system using ultrasonic wave. The positioning problem is an important part of control problem for unmanned navigation of a vehicle. Dead Reckoning is widely used for positioning of vehicle. However this method has problems because it accumulates estimation errors. We propose a new method to increase the accuracy of position estimation using the Ultrasonic Satellite System (USAT). It is shown that we will be able to estimate the position of vehicle precisely, in which errors are not accumulated. And proposed trajectory tracking control methods include both a new path planning method and a lateral control method for vehicle. The experimental results show that the proposed methods enables exact vehicle trajectory tracking even under various environmental factors.

• The Journal of Korea Robotics Society
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• v.5 no.1
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• pp.55-63
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• 2010

This paper describes performance improvement of GPS/DR Integration system using area decision algorithm and vehicle movement information. In GPS signal blockage area, i.e., tunnel and underground parking area, DR sensor errors are accumulated and navigation solution is gradually diverged. We use the car movement information according to moving area to correct the DR sensor error. Also, vehicle movement is decided as stop, straight line, turn and movement changing region through DR sensor data analysis. The car experiment is performed to verify the supposed method. The results show that supposed method provides small position and heading error than previous method.

• International Journal of Control, Automation, and Systems
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• v.2 no.4
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• pp.485-493
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• 2004

Open-loop position estimation methods are commonly used in mobile robot applications. Their strength lies in the speed and simplicity with which an estimated position is determined. However, these methods can lead to inaccurate or unreliable estimates. Two position estimation methods are developed in this paper, one using a single optical flow sensor and a second using two optical sensors. The first method can accurately estimate position under ideal conditions and also when wheel slip perpendicular to the axis of the wheel occurs. The second method can accurately estimate position even when wheel slip parallel to the axis of the wheel occurs. Location of the sensors is investigated in order to minimize errors caused by inaccurate sensor readings. Finally, a method is implemented and tested using a potential field based navigation scheme. Estimates of position were found to be as accurate as dead-reckoning in ideal conditions and much more accurate in cases where wheel slip occurs.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10a
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• pp.787-792
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• 1991

This paper proposes a steering control algorithm for non-holonomic mobile robots. The steering control algorithm is essential to navigate autonomous vehicles which employ comination of the dead reckoning and absolute sensor system such as a machine vison for detecting landmarks in order to estimate the current location of the mobile robot. The proposed algorithm is based on the minimum time BANG-BANG controller and curvature-continuity curve design method. In the BANG-BANG control scheme we introduce velocity/acceleration limiter to avoid any slippage of driving wheels. The proposed scheme is robot-independent and hence can be applied to various kinds of mobile robot or vehicles. To show the effectness of the proposed control algorithm, a series of computer simulations were conducted for two-wheel driven mobile robot.

• Proceedings of the KIEE Conference
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• 1999.07g
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• pp.3086-3088
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• 1999

An ultrasonic sensor is one of most popular sensor used to navigate mobile robots within environments containing obstacles. But many navigation algorithm have studied because of the drawback of ultrasonic sensor such that poor directionality, frequent misreadings, specular reflections. Also, the most crucial drawback of this algorithm, that is VFF, VFM, EDM, PFM, WFM, GFM etc. has been that the mobile robot may become trapped in a local minimum. In this paper, we present a theoretical study of a navigation algorithm which integrals a heuristic-search local minimum (or trap) recovery method with a vector-field based method to maneuver cylindric mobile robots in unknown of unstructured environments. Also, an autonomous mobile robot uses dead-reckoning to estimate the current position and orientation of a mobile robot.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.19 no.1
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• pp.94-106
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• 2020

Recently, the radio navigation method utilizing the GPS(Global Positioning System) satellite information is widely used as the method to measure the position of objects. As GPS applications become wider and fields based on various positioning information emerge, new methods for achieving higher accuracy are required. In the case of autonomous vehicles, the INS(Inertial Navigation System) using the IMU(Inertial Measurement Unit), and the DR(Dead Reckoning) algorithm using the in-vehicle sensor, are used for the purpose of preventing degradation of accuracy of the GPS and to measure the position in the shadow area. However, these positioning methods have many elements of problems due not only to the existence of various shaded areas such as building areas that are continually enlarged, tunnels, underground parking lots and but also to the limitations of accumulation-based location estimation methods that increase in error over time. In this paper, an efficient positioning method in a large underground parking space using Fingerprint method is proposed by placing the AP(Access Points) and directional antennas in the form of four anchors using WLAN, a popular means of wireless communication, for positioning the vehicle in the GPS shadow area. The proposed method is proved to be able to produce unchanged positioning results even in an environment where parked vehicles are moved as time passes.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.36 no.5
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• pp.395-401
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• 2018

Recently, most of mobile devices are equipped with GNSS (Global Navigation Satellite System). When the GNSS signal is available, it is easy to obtain position information. However, GNSS is not suitable solution for indoor localization, since the signals are normally not reachable inside buildings. A wide varieties of technology have been developed as a solution for indoor localization such as Wi-Fi, beacons, and inertial sensor. With the increased sensor combinations in mobile devices, mobile devices also became feasible to provide a solution, which based on PDR (Pedestrian Dead Reckoning) method. In this study, we utilized the combination of three sensors equipped in mobile devices including accelerometer, digital compass, and gyroscope and applied three representative PDR methods. The proposed methods are done in three stages; step detection, step length estimation, and heading determination and the final indoor localization result was evaluated with terrestrial LiDAR (Light Detection And Ranging) data obtained in the same test site. By using terrestrial LiDAR data as reference ground truth for PDR in two differently designed experiments, the inaccuracy of PDR methods that could not be found by existing evaluation method could be revealed. The firstexperiment included extreme direction change and combined with similar pace size. Second experiment included smooth direction change and irregular step length. In using existing evaluation method which only checks traveled distance, The results of two experiments showed the mean percentage error of traveled distance estimation resulted from three different algorithms ranging from 0.028 % to 2.825% in the first experiment and 0.035% to 2.282% in second experiment, which makes it to be seen accurately estimated. However, by using the evaluation method utilizing terrestrial LiDAR data, the performance of PDR methods emerged to be inaccurate. In the firstexperiment, the RMSEs (Root Mean Square Errors) of x direction and y direction were 0.48 m and 0.41 m with combination of the best available algorithm. However, the RMSEs of x direction and y direction were 1.29 m and 3.13 m in the second experiment. The new evaluation result reveals that the PDR methods were not effective enough to find out exact pedestrian position information opposed to the result from existing evaluation method.

• 전자공학회논문지 IE
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• v.43 no.4
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• pp.128-135
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• 2006

This paper proposes the control method of fuzzy based sensor fusion by using the self localization of environment, position data by dead reckoning of the encoder and world map from sonic sensors. The proposed fuzzy based sensor fusion system recognizes the object and extracts features such as edge, distance and patterns for generating the world map and self localization. Therefore, this paper has developed fuzzy based control of mobile robot with experimentations in a corridor environment.

• Journal of Institute of Control, Robotics and Systems
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• v.2 no.4
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• pp.330-336
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• 1996

An real-time active beacon localization system for mobile robots is developed and implemented. This system permits the estimation of robot positions when detecting light sources by PSD(Position Sensitive Detector) sensor which are placed sparsely over the robots work space as beacons(or landmarks). An LSE(Least Square Estimation) method is introduced to calibrate the internal parameters of a model for the beacon and robot position. The proposed system has two operational modes of position estimation. One is the initial position calculation by the detection of two or more light sources positions of which are known. The other is the continuous position compensation that calculates the position and heading of the robot using the IEKF(Iterated Extended Kalman Filter) applied to the beacon and dead-reckoning data. Practical experiments show that the estimated position obtained by this system is precise enough to be useful for the navigation of robots.