scispace - formally typeset
Search or ask a question
Author

Young Min Yoo

Bio: Young Min Yoo is an academic researcher from Seoul National University. The author has contributed to research in topics: Inertial navigation system & Navigation system. The author has an hindex of 5, co-authored 8 publications receiving 103 citations.

Papers
More filters
Proceedings ArticleDOI
25 Sep 2009
TL;DR: This paper investigates RFID read latency and thus effectiveness of on-vehicles reader installations for a wide range of speeds, and experimentally studies the impact of reader and tag relative positions on read errors and read rates.
Abstract: Due to recent technology advancements, RFID readers have been proposed for several vehicular applications ranging from safe navigation to intelligent transport. However, one obstacle to deployment is the unpredictable read performance. An RFID reader occasionally fails to read an RFID tag even in static circumstances, mostly due to collisions. In a mobile vehicular environment, latency becomes the key performance factor because of the high speed of vehicles. This is particularly true when the RFID reader is on the moving vehicle. In this paper, we investigate RFID read latency and thus effectiveness of on-vehicles reader installations for a wide range of speeds. First, we experimentally study the impact of reader and tag relative positions on read errors and read rates. Then we conduct road experiments at varying speeds. The results reveal the critical factors that influence on-vehicle RFID read performance, and give us guidance to identify and pursue directions for improvement.

56 citations

Journal ArticleDOI
TL;DR: In this article, a new Kalman filter method is proposed for roll and pitch attitude estimation in ARS using three gyros and three accelerometers, gyro drift must be compensated with accelerometer to avoid divergence of attitude error.
Abstract: To calculate the attitude in ARS(Attitude Reference System) using 3 gyros and 3 accelerometers, gyro drift must be compensated with accelerometer to avoid divergence of attitude error. Kalman filter is most popular method to integrate those two sensor outputs. In this paper, new Kalman filtering method is proposed for roll and pitch attitude estimation. New states are defined to make linear equation and algorithm for changing Kalman filter parameters is proposed to ignore disturbances of acceleration. This algorithm can be easily applied to low cost ARS.

18 citations

Proceedings ArticleDOI
23 Apr 2012
TL;DR: An improved TERCOM aided INS algorithm is proposed which corrects the velocity error of INS using linear Kalman filter, even though the navigation system does not have a speedometer and can prevent divergence of navigation solution based on computer simulations.
Abstract: TERCOM is a terrain referenced navigation system using batch processing method which determines vehicle's current position by comparing a series of terrain height measurements with database. Generally, it is known that TERCOM operates well over terrain with high roughness. However, if the attitude and velocity error of INS is not corrected, the navigation solution of conventional TERCOM aided INS can diverge. This paper describes the TERCOM aided INS algorithm and show the divergence problem. To solve the problem, we propose an improved TERCOM aided INS algorithm which corrects the velocity error of INS using linear Kalman filter, even though the navigation system does not have a speedometer. It is shown that the proposed TERCOM algorithm can prevent divergence of navigation solution based on computer simulations.

16 citations

Journal ArticleDOI
TL;DR: In this paper, a theoretical method for analyzing the observability of a strapdown inertial navigation system (SDINS) integrated with the global positioning system (GPS) is proposed.
Abstract: A theoretical method for analyzing the observability of a strapdown inertial navigation system (SDINS) integrated with the global positioning system (GPS) is proposed. The analysis is performed based on two types of maneuvers for a vehicle on a horizontal trajectory: level flight with constant north velocity and level flight with constant east velocity. The observability also is analyzed using the convergence theorem, stationary state observability analysis results, and Kalman filter measurement information to rearrange the SDINS error model equation. The state variables are divided into observable and unobservable parts, and determine which state variables are observable and estimable with some errors from the relationship of observable and unobservable state variables. Our results have shown that the north and east axes accelerometer bias errors were unobservable, and that attitude errors, and east and down axes gyro bias errors were estimable with some unknown bias errors. It has been shown that horizontal maneuvering improves the observability of down axis gyro bias error compared with the stationary state, and the estimation errors of the heading error state and east axis gyro bias error are dependent on the magnitude of north velocity. The results of the theoretical observability analysis are confirmed through computer simulation.

11 citations

Journal ArticleDOI
TL;DR: Results show that the TRN/INS integrated algorithm, even when the initial INS error is present, overcomes the shortcomings of linear profile-based TRN and improves navigation performance.
Abstract: In recent years alternative navigation system such as a DBRN (Data-Base Referenced Navigation) system using geophysical information is getting attention in the military navigation systems in advanced countries. Specifically TRN (Terrain Referenced Navigation) algorithm research is important because TRN system is a practical DBRN application in South Korea at present time. This paper presents an integrated navigation algorithm that combines a linear profile-based TRN and INS (Inertial Navigation System). We propose a correlation analysis method between TRN performance and terrain roughness index. Then we propose a conditional position update scheme that utilizes the position output of the conventional linear profile type TRN depending on the terrain roughness index. Performance of the proposed algorithm is verified through Monte Carlo computer simulations using the actual terrain database. The results show that the TRN/INS integrated algorithm, even when the initial INS error is present, overcomes the shortcomings of linear profile-based TRN and improves navigation performance.

6 citations


Cited by
More filters
Proceedings ArticleDOI
06 Mar 2014
TL;DR: The evolution from Intelligent Vehicle Grid to Autonomous, Internet-connected Vehicles, and Vehicular Cloud is discussed, the equivalent of Internet cloud for vehicles, providing all the services required by the autonomous vehicles.
Abstract: Traditionally, the vehicle has been the extension of the man's ambulatory system, docile to the driver's commands. Recent advances in communications, controls and embedded systems have changed this model, paving the way to the Intelligent Vehicle Grid. The car is now a formidable sensor platform, absorbing information from the environment (and from other cars) and feeding it to drivers and infrastructure to assist in safe navigation, pollution control and traffic management. The next step in this evolution is just around the corner: the Internet of Autonomous Vehicles. Pioneered by the Google car, the Internet of Vehicles will be a distributed transport fabric capable to make its own decisions about driving customers to their destinations. Like other important instantiations of the Internet of Things (e.g., the smart building), the Internet of Vehicles will have communications, storage, intelligence, and learning capabilities to anticipate the customers' intentions. The concept that will help transition to the Internet of Vehicles is the Vehicular Cloud, the equivalent of Internet cloud for vehicles, providing all the services required by the autonomous vehicles. In this article, we discuss the evolution from Intelligent Vehicle Grid to Autonomous, Internet-connected Vehicles, and Vehicular Cloud.

610 citations

01 Jan 2003
TL;DR: The Colorwave algorithm is presented, a simple, distributed, on-line algorithm for the reader collision problem in radio frequency identification (RFID) systems that enables the RFID system to automatically adapt to changes in the system and in the operating environment of the system.
Abstract: We present the Colorwave algorithm, a simple, distributed, on-line algorithm for the reader collision problem in radio frequency identification (RFID) systems. RFID systems are increasingly being used in applications, such as those experienced in supply chain management, which require RFID readers to operate in close proximity to one another. Readers physically located near one another may interfere with one another's operation. Such reader collisions must be minimized to ensure the correct operation of the RFID system. The Colorwave algorithm yields on-line solutions that are near the optimal static solutions. The dynamic nature of the algorithm enables the RFID system to automatically adapt to changes in the system and in the operating environment of the system.

294 citations

Journal ArticleDOI
TL;DR: The evolution from intelligent vehicle grid to autonomous, Internet-connected vehicles, and vehicular fog is discussed, the equivalent of instantaneous Internet cloud for vehicles, providing all the services required by the autonomous vehicles.
Abstract: Recent advances in communications, controls, and embedded systems have changed the perception of a car. A vehicle has been the extension of the man's ambulatory system, docile to the driver's commands. It is now a formidable sensor platform, absorbing information from the environment (and from other cars) and feeding it to drivers and infrastructure to assist in safe navigation, pollution control, and traffic management. The next step in this evolution is just around the corner: the Internet of Autonomous Vehicles. Pioneered by the Google car, the Internet of Vehicles will be a distributed transport fabric capable of making its own decisions about driving customers to their destinations. Like other important instantiations of the Internet of Things (e.g. the smart building), the Internet of Vehicles will have communications, storage , intelligence, and learning capabilities to anticipate the customers' intentions. The concept that will help transition to the Internet of Vehicles is the vehicular fog, the equivalent of instantaneous Internet cloud for vehicles, providing all the services required by the autonomous vehicles. In this article, we discuss the evolution from intelligent vehicle grid to autonomous, Internet-connected vehicles, and vehicular fog.

148 citations

01 Nov 2004
TL;DR: The design of a modular system for untethered real-time kinematic motion capture using sensors with inertial measuring units (IMU) is described, which is comprised of a set of small and lightweight sensors.
Abstract: We describe the design of a modular system for untethered real-time kinematic motion capture using sensors with inertial measuring units (IMU). Our system is comprised of a set of small and lightweight sensors. Each sensor provides its own global orientation (3 degrees of freedom) and is physically and computationally independent, requiring only external communication. Orientation information from sensors is communicated via wireless to host computer for processing. We present results of the real-time usage of our untethered motion capture system for teleoperating the NASA Robonaut. We also discuss potential applications for untethered motion capture with respect to humanoid robotics.

112 citations

Journal ArticleDOI
TL;DR: In this article, the authors proposed an e-pedigree food traceability system, utilizing radio frequency identification technology to track and trace product location and wireless sensor network to collect temperature and humidity during storage and transportation.

104 citations