• Journal of the Korean Society for Precision Engineering
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• v.29 no.7
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• pp.762-769
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• 2012

The localization system for tour guide robot was developed which is inevitable and important for the guide robot in order to guide the tourists and explain the history or contents of the site. The localization system is based on the non-inertial sensors such as a DGPS, Dead-Reckoning. The information of the DGPS is used to update the estimated positions from Dead Reckoning. The extended Kalman filter was used for the fusion of the measured information from the sensors and estimated positions by Dead Reckoning. The simulation results show that it is very reliable and the position error is bounded within a certain extend.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.82-82
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• 2000

The way which estimates a position from Navigation is Dead-reckoning Navigation and Radio Navigation. Generally dead-reckoning navigation uses Gyro and odometer as sensor, but these have problems which are an integrating noise and a noise-sensitivity. Gps which is used by radio-navigation has a Troposthetic error and MultiPath ewer and so on. For minimizing a Troposthetic error and a Multipath error, this paper suggests to an algorithm which use vanishing point on CCD camera.

• ETRI Journal
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• v.32 no.6
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• pp.891-900
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• 2010

In this paper, a map-matching (MM) algorithm which combines an estimated position with digital road data is proposed. The presented algorithm using a virtual track is appropriate for a MEMS-based pedestrian dead reckoning (PDR) system, which can be used in mobile devices. Most of the previous MM algorithms are for car navigation systems and GPS-based navigation system, so existing MM algorithms are not appropriate for the pure DR-based pedestrian navigation system. The biggest problem of previous MM algorithms is that they cannot determine the correct road segment (link) due to the DR characteristics. In DR-based navigation system, the current position is propagated from the previous estimated position. This means that the MM result can be placed on a wrong link when MM algorithm fails to decide the correct link at once. It is a critical problem. Previous algorithms never overcome this problem because they did not consider pure DR characteristics. The MM algorithm using the virtual track is proposed to overcome this problem with improved accuracy. Performance of the proposed MM algorithm was verified by experiments.

• Journal of Institute of Control, Robotics and Systems
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• v.7 no.5
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• pp.454-464
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• 2001

In this paper, a personal navigation system is developed using GPS and dead reckoning sensors. This personal navigation system can be used to track a person inside a building, on an urban street, and in the mountain area. GPS can provide accurate absolute position information, but it cant be used without receiving enough satellite signals. Although the inertial sensors such as gyro an accelerometer and be used without this diggiculty, the inertial sensors severely suffer from their drift errors and the magne-tometer can be easily distorted by surrounding electromagnetic field. GPS and DR sensors can be inte-grated together to overcome these problems. A new personal navigation system that can be carried wit person is developed. A pedometer. actually vertically mounted accelerometer, detects ones footstep and gyro detects heading angle. These DR sensors are integrated with GPS and the humans walking pattern provides additional navigation information for compensating the DR sensors. The field testes are performed to evaluated the proposed navigation algorithm.

• Journal of Sensor Science and Technology
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• v.28 no.6
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• pp.345-354
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• 2019

The 3D position of pedestrians is a physical quantity used in various fields, such as automotive navigation and augmented reality. An inertial navigation system (INS) based pedestrian dead reckoning (PDR), hereafter INS-PDR, estimates the relative position of pedestrians using an inertial measurement unit (IMU). Since an INS-PDR integrates the accelerometer signal twice, cumulative errors occur and cause a rapid increase in drifts. Various correction methods have been proposed to reduce drifts. For example, one of the most commonly applied correction method is the zero velocity update (ZUPT). This study investigated the characteristics of the existing INS-PDR methods based on shoe-mounted IMU and compared the estimation performances under various conditions. Four methods were chosen: (i) altitude correction (AC); (ii) step length correction (SLC); (iii) advanced heuristic drift elimination (AHDE); and (iv) magnetometer-based heading correction (MHC). Experimental results reveal that each of the correction methods shows condition-sensitive performance, that is, each method performs better under the test conditions for which the method was developed than it does under other conditions. Nevertheless, AC and AHDE performed better than the SLC and MHC overall. The AC and AHDE methods were complementary to each other, and a combination of the two methods yields better estimation performance.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.11
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• pp.1189-1195
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• 2008

We introduce a MEMS-based pedestrian dead reckoning (PDR) system. A walking navigation algorithm for pedestrians is presented and map-matching algorithm for the navigation system based on dead reckoning (DR) is proposed. The PDR is equipped on the human body and provides the position information of pedestrians. And this is able to be used in ubiquitous sensor network (USN), U-hearth monitoring system, virtual reality (VR) and etc. The PDR detects a step using a novel technique and simultaneously estimates step length. Also an azimuth of the pedestrian is calculated using a fluxgate which is the one of magnetometers. Map-matching algorithm can be formulated to integrate the positioning data with the digital road network data. Map-matching algorithm not only enables the physical location to be identified from navigation system but also improves the positioning accuracy. However most of map-matching algorithms which are developed previously are for the car navigation system (CNS). Therefore they are not appropriate to implement to pedestrian navigation system based on DR system. In this paper, we propose walking navigation system and map-matching algorithm for PDR.

• Proceedings of the KIEE Conference
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• 2005.10b
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• pp.597-599
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• 2005

To make the autonomous mobile robot move in the unknown space, we have to know the information of current location of the robot. So far, the location information that was obtained using Encoder always includes Dead Reckoning Error, which is accumulated continuously and gets bigger as the distance of movement increases. In this paper, we analyse the effect of the size of the two wheels of the mobile robot and the wheel track of them among the factors of Dead Reckoning Error. And after this, we compensate this Dead Reckoning Error by Kalman filter using Gyro Sensors. To accomplish this, we develop the controller to analyse the error components of Gyro Sensor and to minimize the error values. We employ the numerical approach to analyse the error components by linearizing them because each error component is nonlinear. And we compare the improved result through simulation.

• Journal of Positioning, Navigation, and Timing
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• v.9 no.2
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• pp.117-124
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• 2020

In this paper, the symmetric position drift of the integration approach in pedestrian dead reckoning (PDR) system with dual foot-mounted IMU is analyzed. The PDR system that uses the inertial sensor attached to the shoe is called the IA-based PDR system. Since this system is designed based on the inertial navigation system (INS), it has the same characteristics as the error of the INS, then zero-velocity update (ZUPT) is used to correct this error. However, an error that cannot be compensated perfectly by ZUPT exists, and the trend of the position error is the symmetric direction along the side of the shoe(left, right foot) with the IMU attached. The symmetric position error along the side of the shoe gradually increases with walking. In this paper, we analyze the causes of symmetric position drift and show the results. It suggests the possibility of factors other than the error factors that are generally considered in the PDR system based on the integration approach.

• Journal of Advanced Navigation Technology
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• v.14 no.5
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• pp.648-654
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• 2010

In this paper, a navigation system was designed, and performance tested in order to confirm the safety improvement of the GNSS(Global Navigation Satellite System)-based AGV(Autonomous Guided Vehicle) which used only position information on of GNSS. We developed DR(Dead Reckoning) navigation system that involve the use of GNSS abnormal positoning error detection and GNSS signal outage. The test results show that GNSS positioning error is detection can be archived with an error of more than 0.15m. In addition, the DR driving position error is 1.5m for an 8s GNSS positioning service outage.

• Journal of applied mathematics & informatics
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• v.27 no.3_4
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• pp.703-714
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• 2009

GPS is especially suitable for location systems in flat areas, but the availability of GPS is limited in highly urbanized and mountain areas, due to the nature of satellite communications. Dead reckoning is generally used to solve a location problem when a pedestrian is out of range of GPS coverage. To extend the apparent coverage of the GPS system for a hiker in mountain areas, we propose an integrated 3D location system that interpolates a 3D dead reckoning system based on information about contour lines. The speeds of hikers vary according to the inclination of the ground in sloped areas such as mountains. To reduce location measurement errors, we determine the angle of inclination based on the contour lines of the mountain, and use the speeds based on the inclination in the location system. The simulation results show that the proposed system is more accurate than the existing location system.