• Journal of Korea Spatial Information System Society
• /
• v.11 no.1
• /
• pp.183-188
• /
• 2009

In this paper, we preset a method for the development of u-GIS outdoor augmented reality(AR) system. The proposed system is consist of three parts. First, sensor acquisition and calibration for AR, Second, camera and sensor based tracking for AR, Third, integration of sensor information and 3D models. We combine spatial information of real and virtual spaces through u-GIS AR system.

• Journal of Institute of Control, Robotics and Systems
• /
• v.15 no.8
• /
• pp.845-850
• /
• 2009

Localization which estimates a robot's position and orientation in a given environment is very important for mobile robot navigation. Although low-cost sensors are preferred for practical service robots, they suffer from the inaccurate and insufficient range information. This paper proposes a novel approach to increasing the success rate of low-cost sensor-based localization. In this paper, both the previous and the current data obtained from the IR sensors are used for localization in order to utilize as much environment information as possible without increasing the number of sensors. The sensor model used in the monte carlo localization (MCL) is modified so that the accumulated range information may be used to increase the accuracy in estimating the current robot pose. The experimental results show that the proposed method can robustly estimate the robot's pose in indoor environments with several similar places.

• Journal of Industrial Technology
• /
• v.19
• /
• pp.173-178
• /
• 1999

In many areas of technology there are machines and systems controllable in up to six degrees of freedom. Helicopters and underwater vehicles, industrial robots are among the first representatives of this category. They need six degrees of freedom in order to move and orient within their workspace. An even broader and more explosively growing area is 3D computer graphics and virtual environment. In this work, functions of 3D input device are described and two types of commercial 3D input device are presented. Then, a preliminary experiment of a low cost 6 axis force/moment sensor is presented that can also be sued as a 3D input device. A low cost force/moment sensor and its application in robot teaching experiment is described. It computes the direction of 3 components of the force and 3 components of the moment applied by human holding the sensor by hand. The concept is shown by an experiment where the tool position and orientation of a robot in 3 dimensional space is controlled by the proposed sensor.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2012.04a
• /
• pp.860-863
• /
• 2012

본 논문에서는 지각의 실시간 측량과 데이터 수집을 위해 Gyro Sensor기반의 전자기준점 시스템을 제안한다. 이를 위해 GPS 모듈, 환경 센서 및 Gyro Sensor를 이용하여 측량값을 데이터화하고 데이터값을 CDMA 모듈 방식을 이용해 데이터베이스 서버로 전송한다. 또한 측정값을 사용자 기반의 시스템 GUI를 구현함으로써 실시간으로 모니터링이 가능하도록 구현하였다.

• Journal of Auto-vehicle Safety Association
• /
• v.13 no.4
• /
• pp.114-122
• /
• 2021

In this paper, an automated vehicle intersection collision accident was analyzed through simulation. Recently, the more automated vehicles are distributed, the more accidents related to automated vehicles occur. Accidents may show different trends depending on the sensor characteristics of the automated vehicle and the performance of the accident prevention system. Based on NASS-CDS (National Automotive Sampling System-Crashworthiness Data System) and TAAS (Traffic Accident Analysis System), four scenarios are derived and simulations are performed. Automated vehicles are applied with a virtual system consisting of an autonomous emergency braking system and algorithms that predict the route and avoid collisions. The simulations are conducted by changing the sensor angle, vehicle speed, the range of the sensor and vehicle speed range. A range of variables considered vehicle collision were derived from the simulation.

• Journal of Auto-vehicle Safety Association
• /
• v.14 no.1
• /
• pp.20-25
• /
• 2022

This paper presents a development of simulation environment for validation of autonomous driving (AD) algorithm based on Robot Operating System (ROS). ROS is one of the commonly-used frameworks utilized to control autonomous vehicles. For the evaluation of AD algorithm, a 3D autonomous driving simulator has been developed based on LGSVL. Two additional sensors are implemented in the simulation vehicle. First, Lidar sensor is mounted on the ego vehicle for real-time driving environment perception. Second, GPS sensor is equipped to estimate ego vehicle's position. With the vehicle sensor configuration in the simulation, the AD algorithm can predict the local environment and determine control commands with motion planning. The simulation environment has been evaluated with lane changing and keeping scenarios. The simulation results show that the proposed 3D simulator can successfully imitate the operation of a real-world vehicle.

• KIPS Transactions on Software and Data Engineering
• /
• v.8 no.12
• /
• pp.491-498
• /
• 2019

Digital twin is a technology that virtualizes physical objects of the real world on a computer. It is used by collecting sensor data through IoT, and using the collected data to connect physical objects and virtual objects in both directions. It has an advantage of minimizing risk by tuning an operation of virtual model through simulation and responding to varying environment by exploiting experiments in advance. Recently, artificial intelligence and machine learning technologies have been attracting attention, so that tendency to virtualize a behavior of physical objects, observe virtual models, and apply various scenarios is increasing. In particular, recognition of each robot's motion is needed to build digital twin for co-robot which is a heart of industry 4.0 factory automation. Compared with modeling based research for recognizing motion of co-robot, there are few attempts to predict motion based on sensor data. Therefore, in this paper, an experimental environment for collecting current and inertia data in co-robot to detect the motion of the robot is built, and a motion prediction model based on the collected sensor data is proposed. The proposed method classifies the co-robot's motion commands into 9 types based on joint position and uses current and inertial sensor values to predict them by accumulated learning. The data used for accumulating learning is the sensor values that are collected when the co-robot operates with margin in input parameters of the motion commands. Through this, the model is constructed to predict not only the nine movements along the same path but also the movements along the similar path. As a result of learning using SVM, the accuracy, precision, and recall factors of the model were evaluated as 97% on average.

• Proceedings of the KIPE Conference
• /
• 2001.10a
• /
• pp.369-373
• /
• 2001

Multilevel inverter has attracted great interest in high-voltage high-power field because of its less distorted output. In this paper, a direct torque control (DTC) technique based on a three-level neutral-point-clamped (NPC) inverter is presented. In order to solve the intrinsic neutral-point voltage-balancing problem and to obtain a high performance DTC, a special vector selection method is introduced and the concept of virtual vector is developed. By using the proposed PWM strategy, a MRAS speed sensor-less DTC drive can be achieved without sensing the neutral-point voltage, The strategy can be verified by simulation and experimental results.

• Proceedings of the Korean Information Science Society Conference
• /
• 2011.06b
• /
• pp.17-20
• /
• 2011

This paper presents an approach for integrating u-Life care applications into the Cloud computing based on virtual resources to support real-time services and to improve quality of service (QoS) requirement. We propose an architecture for virtualization resources scheduling. The proposed is based on the concepts of Cloud computing and Wireless sensor networks. In this paper, we focus on the scheduling u-Life care applications run on the virtual machine (VM) resources in Cloud computing.

• IE interfaces
• /
• v.23 no.3
• /
• pp.229-238
• /
• 2010

Virtual metrology (VM), a critical component of semiconductor manufacturing, is an efficient way of assessing the quality of wafers not actually measured. This is done based on a model between equipment sensor data (obtained for all wafers) and the quality characteristics of wafers actually measured. This paper considers principal component regression (PCR), partial least squares regression (PLSR), kernel PCR (KPCR), and kernel PLSR (KPLSR) as VM models. For each regression model, two cases are considered. One utilizes all explanatory variables in developing a model, and the other selects significant variables using the genetic algorithm (GA). The prediction performances of 8 regression models are compared for the short- and long-term etch process data. It is found among others that the GA-KPLSR model performs best for both types of data. Especially, its prediction ability is within the requirement for the short-term data implying that it can be used to implement VM for real etch processes.