• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.10C
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• pp.956-963
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• 2006

This research studies multi participant consistency and dynamic data shared through 3D scenes in virtual network environments. In a distributed virtual environment of client-server structure, consistency is maintained by the static information exchange; as jerks occur by packet delay when updating messages of dynamic data exchanges are broadcasted frequence, the network bottleneck is reduced by predicting the movement path by using the Dead-reckoning algorithm. In Dynamic data path prediction, the tests the location prediction error between Dead-reckoning convergence interval and error of prediction and actual condition one time above threshold it interpolates a previously location. The shared dynamic data of the 3D virtual environment is implementation using the VRML EAI.

• Journal of Advanced Marine Engineering and Technology
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• v.24 no.1
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• pp.119-126
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• 2000

In constructing the positioning system based on a conventional dead-reckoning for a wheeled vehicle with pneumatic tires, the position estimation error is inevitable as changes of the radius of the wheels depend on live load and variable enviroment. Therefore, this paper proposes the positioning system which can estimate the error source i.e. the vehicle parameter errors, such as the right and left wheel radius error, using gyroscope and ultrasonic sensor and correct the parameter to reduce the dead-reckoned position estimation error. The extended Kalman filter was used as a method for the multisensor data fusion. The simulation to verify the effectiveness of the proposed positioning system is performed.

• IEMEK Journal of Embedded Systems and Applications
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• v.4 no.2
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• pp.69-78
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• 2009

Localization is a very important technique for the mobile robot to navigate in outdoor environment. In this paper, the development of the sensor fusion algorithm for controlling mobile robots in outdoor environments is presented. The multi-sensorial dead-reckoning subsystem is established based on the optimal filtering by first fusing a heading angle reading data from a magnetic compass, a rate-gyro, and two encoders mounted on the robot wheels, thereby computing the dead-reckoned location. These data and the position data provided by a global sensing system are fused together by means of an extended Kalman filter. The proposed algorithm is proved by simulation studies of controlling a mobile robot controlled by a backstepping controller and a cascaded controller. Performances of each controller are compared.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.241-244
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• 1997

A dead reckoning navigation system is developed for autonomous mobile robot localization. The navigation system was implemented by novel sensor fusion using a Kalman filter. A differential encoder and the gyroscope error models are developed for the filter. An indirect Kalman filter scheme is adopted to reduce the computational burden and to enhance the navigation system reliability. The filter mutually compensates the encoder errors and the gyroscope errors. The experimental results show that the proposed mobile . robot navigation algorithm provides the reliable position and heading angle of the mobile robot without any help of the external positioning systems.

• IEIE Transactions on Smart Processing and Computing
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• v.4 no.3
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• pp.173-182
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• 2015

A real-time, Indoor navigation systems utilize ultra-wide band (UWB), radio-frequency identification (RFID) and received signal strength (RSS) techniques that encompass WiFi, FM, mobile communications, and other similar technologies. These systems typically require surplus infrastructure for their implementation, which results in significantly increased costs and complexity. Therefore, as a solution to reduce the level of cost and complexity, an inertial measurement unit (IMU) and quick response (QR) codes are utilized in this paper to facilitate navigation with the assistance of a smartphone. The QR code helps to compensate for errors caused by the pedestrian dead reckoning (PDR) algorithm, thereby providing more accurate localization. The proposed algorithm having IMU in conjunction with QR code shows an accuracy of 0.64 m which is higher than existing indoor navigation techniques.

• Journal of Institute of Control, Robotics and Systems
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• v.5 no.3
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• pp.306-313
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• 1999

To measure the accurate position of mobile robot, dead-reckoning method using the encoder attached to each wheel is conventionally used, since it is easy to compute and inexpensive to develop. However, that method is useless when slip occurs and error is accumulated with time. This paper proposes a position estimation method using encoder trailer composed of 2 encoders only(ET-2). This method provides accurate position information even when slip occurs, and can reduce accumulated error if we select the proper link lengths of encoder trailer. Experimental results show the performance of ET-2 when slip occurs. Finally, accumulated systematic error from encoder resolution is analyzed in comparison with an existing method with encoder trailer composed of 3 encoders. (As a matter of convenience, we will call the existing encoder trailer ‘ET-3’)

• The Journal of Korea Robotics Society
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• v.5 no.4
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• pp.349-358
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• 2010

We presents a dynamic modeling of 4-wheel 2-DOF. WMR. The classic dynamic model utilizes a greatly simplified wheel motion representation and using of a simplified dynamic model confronts with a problem for accurate position control of wheeled mobile robot. In this paper, we treats the dynamic model for describes relationship between the wheel actuator force/torque and WMR motion through the use of Newton's equilibrium laws. To calculate the WMR position in real time, we introduced the Dead-Reckoning algorithms and the simulation result show that the proposed dynamic model is useful. We can be easily extend the proposed WMR model to mobile robot of similar type and this type of methodology is useful to analyze, design and control any kinds of rolling robots.

• Proceedings of the KIEE Conference
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• 2006.10c
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• pp.560-562
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• 2006

In this paper, Correct problem in dead reckoning system and proposed about position error revision techniques of mobile robot to use RFID tag for position awareness. With the dead reckoning system, as the accumulation of error are unavoidable because of accumulation of informations as the time passage, so it is impossible to get correct information about posture, including torrent direction, movement distance, etc. As one of compensation method, the suggested method is that after selecting special area (corridor), compensate absolute location information by arranging two line of RFID tag along two side of corridor. Through this suggested method, it could be used when robot wants to move in limited areas.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.256-261
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• 2005

In this research, we propose a path-planning algorithm for an autonomous mobile robot using geographical information, under the condition that the robot moves in unknown environment. All image inputted by camera at every sampling time are analyzed and geographical elements are recognized, and the geographical information is embedded in environmental map. The geographical information was transformed into 1-dimensional evaluation value that expressed the difficulty of movement for the robot. The robot goes toward the goal searching for path that minimizes the evaluation value at every sampling time. Then, the path is updated by integrating the exploited information and the prediction on unexploited environment. We used a sensor fusion method for improving the mobile robot dead reckoning accuracy. The experiment results that confirm the effectiveness of the proposed algorithm on the robot's reaching the goal successfully using geographical information are presented.

• International Journal of Ocean System Engineering
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• v.1 no.2
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• pp.102-109
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• 2011

This paper describes the implementation of a precise underwater navigation solution using a multiple sensor fusion technique based on USBL, GPS, DVL and AHRS measurements for the operation of a remotely operated mine disposal vehicle (MDV). The estimation of accurate 6DOF positions and attitudes is the key factor in executing dangerous and complicated missions. To implement the precise underwater navigation, two strategies are chosen in this paper. Firstly, the sensor frame alignment to the body frame is conducted to enhance the performance of a standalone dead-reckoning algorithm. Secondly, absolute position data measured by USBL is fused to prevent cumulative integration error. The heading alignment error is identified by comparing the measured absolute positions with the DR algorithm results. The performance of the developed approach is evaluated with the experimental data acquired by MDV in the South-sea trial.