• Title/Summary/Keyword: Localization strategy

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Fast Time Difference of Arrival Estimation for Sound Source Localization using Partial Cross Correlation

  • Yiwere, Mariam;Rhee, Eun Joo
    • Journal of Information Technology Applications and Management
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    • v.22 no.3
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    • pp.105-114
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    • 2015
  • This paper presents a fast Time Difference of Arrival (TDOA) estimation for sound source localization. TDOA is the time difference between the arrival times of a signal at two sensors. We propose a partial cross correlation method to increase the speed of TDOA estimation for sound source localization. We do this by predicting which part of the cross correlation function contains the required TDOA value with the help of the signal energies, and then we compute the cross correlation function in that direction only. Experiments show approximately 50% reduction in the cross correlation computation time thereby increasing the speed of TDOA computation. This makes it very relevant for real world surveillance.

Fast 360° Sound Source Localization using Signal Energies and Partial Cross Correlation for TDOA Computation

  • Yiwere, Mariam;Rhee, Eun Joo
    • Journal of Information Technology Applications and Management
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    • v.24 no.1
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    • pp.157-167
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    • 2017
  • This paper proposes a simple sound source localization (SSL) method based on signal energies comparison and partial cross correlation for TDOA computation. Many sound source localization methods include multiple TDOA computations in order to eliminate front-back confusion. Multiple TDOA computations however increase the methods' computation times which need to be as minimal as possible for real-time applications. Our aim in this paper is to achieve the same results of localization using fewer computations. Using three microphones, we first compare signal energies to predict which quadrant the sound source is in, and then we use partial cross correlation to estimate the TDOA value before computing the azimuth value. Also, we apply a threshold value to reinforce our prediction method. Our experimental results show that the proposed method has less computation time; spending approximately 30% less time than previous three microphone methods.

An Embedded Solution for Fast Navigation and Precise Positioning of Indoor Mobile Robots by Floor Features (바닥 특징점을 사용하는 실내용 정밀 고속 자율 주행 로봇을 위한 싱글보드 컴퓨터 솔루션)

  • Kim, Yong Nyeon;Suh, Il Hong
    • The Journal of Korea Robotics Society
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    • v.14 no.4
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    • pp.293-300
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    • 2019
  • In this paper, an Embedded solution for fast navigation and precise positioning of mobile robots by floor features is introduced. Most of navigation systems tend to require high-performance computing unit and high quality sensor data. They can produce high accuracy navigation systems but have limited application due to their high cost. The introduced navigation system is designed to be a low cost solution for a wide range of applications such as toys, mobile service robots and education. The key design idea of the system is a simple localization approach using line features of the floor and delayed localization strategy using topological map. It differs from typical navigation approaches which usually use Simultaneous Localization and Mapping (SLAM) technique with high latency localization. This navigation system is implemented on single board Raspberry Pi B+ computer which has 1.4 GHz processor and Redone mobile robot which has maximum speed of 1.1 m/s.

A Study on Strategies of Multinational Bakery Retailers in China : Focused on Paris Baguette and Competitors

  • KIM, Byoung Goo;HWANG, Hee-Joong
    • Journal of Distribution Science
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    • v.18 no.12
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    • pp.55-66
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    • 2020
  • Purpose: For bakery retailers that want to enter the Chinese market, this study seeks to draw implications through the analysis of Paris Baguette, Paul Bakery and local competitors. In particular, the study analyzes entry strategies, as well as the advantages and disadvantages of the companies. Research design, data and methodology: This study analyzed the Chinese bakery industry and overviewed the policy of bakery industry. The research method utilized Chinese Statistical Yearbook of Food Industry and literature related to Chinese bakery industry. Additionally, this study used case analysis methods for foreign and local bakery enterprises in the bakery industry. Results: During the rapid growth of bakery industry, Paris Baguette made a successful settlement by utilizing localization strategy; while on the contrary, Paul Bakery took a standardization strategy and failed in the Chinese market. Conclusions: Paris Baguette succeeded in launching localized products after thoroughly analyzing products that suit local tastes in China. However, Paul Bakery has been knocked out of the Chinese market for failing to capture the taste of the Chinese people by launching standardized products that reproduce French culture and taste. As such, the Chinese market is huge and differences exist in different provinces, so standardization and localization strategies should be appropriately utilized.

Active Audition System based on 2-Dimensional Microphone Array (2차원 마이크로폰 배열에 의한 능동 청각 시스템)

  • Lee, Chang-Hun;Kim, Yong-Ho
    • Proceedings of the KIEE Conference
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    • 2003.11b
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    • pp.175-178
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    • 2003
  • This paper describes a active audition system for robot-human interface in real environment. We propose a strategy for a robust sound localization and for -talking speech recognition(60-300cm) based on 2-dimensional microphone array. We consider spatial features, the relation of position and interaural time differences, and realize speaker tracking system using fuzzy inference profess based on inference rules generated by its spatial features.

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Development of Autonomous Navigation Robot in Outdoor Road Environments (실외 도로 환경에서의 자율주행 로봇 개발)

  • Roh, Chi-Won;Kang, Yeon-Sik;Kang, Sung-Chul
    • Journal of Institute of Control, Robotics and Systems
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    • v.15 no.3
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    • pp.293-299
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    • 2009
  • This paper discusses an autonomous navigation system for urban environments. For the localization of the robot, EKF (Extended Kalman Filter) algorithm is used with odometry, angle sensor, and DGPS (Differential Global Positioning System) measurement. Especially in an urban environment, DGPS is often blocked by buildings and trees and the resulting inaccurate positioning prevents the robot from safe and reliable navigation. In addition to the global information from DGPS, the local information of the curb on the roadway is used to track a route when the global DGPS information is inaccurate. For this purpose, curb detection algorithm is developed and implemented in the developed navigation algorithm. Four different types of navigation strategies are developed and they are switched to adapt to different localization conditions according to the availability of DGPS and the existence of the curbs on the roadway. The experimental results show that the designed switching strategy improves the navigation performance adapting to the environment conditions.

Growth Strategy of PASECO as a Global Electronic Company: Focusing on the Middle East Market

  • KIM, Byoung-Goo;LEE, Chun-Su
    • East Asian Journal of Business Economics (EAJBE)
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    • v.7 no.4
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    • pp.27-40
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    • 2019
  • Purpose - This study aims to analyze PASECO's environment and strategies during its advance into the Middle East to find out the success factors of the kerosene heater market and provide strategic implications for small and medium enterprises' growth based on these factors. Research design and methodology - This study analyzes the success factors of companies operating in the Middle East. As a case analysis study, the method of research analyzes case enterprises through existing literature, newspaper articles, and corporate interview materials. Results - PASECO's success was shown by its high technological power in kerosene heater products, understanding customers' needs, understanding the Middle East market and localization strategy. Conclusions - PASECO has been constantly developing R&D capability to secure competitive products and has released localized products to enhance the satisfaction of its customers in the Middle East and has also been successful by constantly creating new opportunities. The firm's success strategies provide implications for small and medium-sized businesses for greater growth.

Source Localization Techniques for Magnetoencephalography (MEG)

  • Kwang-Ok An;Chang-Hwan Im;Hyun-Kyo Jung;Yong-Ho Lee;Hyuk-Chan Kwon
    • KIEE International Transaction on Systems and Control
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    • v.2D no.2
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    • pp.53-58
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    • 2002
  • In this paper, various aspects in magnetoencephalography (MEG) source localization are studied. To minimize the errors in experimental data, an approximation technique using a polynomial function is proposed. The simulation shows that the proposed technique yields more accurate results. To improve the convergence characteristics in the optimization algorithm, a hybrid algorithm of evolution strategy and sensitivity analysis is applied to the neuromagnetic inverse problem. The effectiveness of the hybrid algorithm is verified by comparison with conventional algorithms. In addition, an artificial neural network (ANN) is applied to find an initial source location quickly and accurately. The simulation indicates that the proposed technique yields more accurate results effectively.

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Ultrasound Echolocation Inspired by a Prey Detection Strategy of Big Brown Bats (박쥐의 먹이 탐지 전략을 모방한 초음파 센서의 물체 위치 추정)

  • Park, Sang-Wook;Kim, Dae-Eun
    • Journal of Institute of Control, Robotics and Systems
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    • v.18 no.3
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    • pp.161-167
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    • 2012
  • It is known that big brown bats can distinguish echo of a prey at various angles. In this paper, we suggest a new object localization strategy using ultrasonic echolocation. We calculate the relative energy ratio between a high frequency component of ultrasound signal and a low frequency component of ultrasound signal for a target object. We found the measure depends on bearing angle of the object in space. We also tested energy ratio of echoed FM ultrasound signals depending on frequency, based on cross-correlation. It can determine the relative angular position of objects even though the reflected signals are congested form each object.

Accurate Human Localization for Automatic Labelling of Human from Fisheye Images

  • Than, Van Pha;Nguyen, Thanh Binh;Chung, Sun-Tae
    • Journal of Korea Multimedia Society
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    • v.20 no.5
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    • pp.769-781
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    • 2017
  • Deep learning networks like Convolutional Neural Networks (CNNs) show successful performances in many computer vision applications such as image classification, object detection, and so on. For implementation of deep learning networks in embedded system with limited processing power and memory, deep learning network may need to be simplified. However, simplified deep learning network cannot learn every possible scene. One realistic strategy for embedded deep learning network is to construct a simplified deep learning network model optimized for the scene images of the installation place. Then, automatic training will be necessitated for commercialization. In this paper, as an intermediate step toward automatic training under fisheye camera environments, we study more precise human localization in fisheye images, and propose an accurate human localization method, Automatic Ground-Truth Labelling Method (AGTLM). AGTLM first localizes candidate human object bounding boxes by utilizing GoogLeNet-LSTM approach, and after reassurance process by GoogLeNet-based CNN network, finally refines them more correctly and precisely(tightly) by applying saliency object detection technique. The performance improvement of the proposed human localization method, AGTLM with respect to accuracy and tightness is shown through several experiments.