• Title/Summary/Keyword: Multi-sensor Tracking

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Appearance Based Object Identification for Mobile Robot Localization in Intelligent Space with Distributed Vision Sensors

  • Jin, TaeSeok;Morioka, Kazuyuki;Hashimoto, Hideki
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.4 no.2
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    • pp.165-171
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    • 2004
  • Robots will be able to coexist with humans and support humans effectively in near future. One of the most important aspects in the development of human-friendly robots is to cooperation between humans and robots. In this paper, we proposed a method for multi-object identification in order to achieve such human-centered system and robot localization in intelligent space. The intelligent space is the space where many intelligent devices, such as computers and sensors, are distributed. The Intelligent Space achieves the human centered services by accelerating the physical and psychological interaction between humans and intelligent devices. As an intelligent device of the Intelligent Space, a color CCD camera module, which includes processing and networking part, has been chosen. The Intelligent Space requires functions of identifying and tracking the multiple objects to realize appropriate services to users under the multi-camera environments. In order to achieve seamless tracking and location estimation many camera modules are distributed. They causes some errors about object identification among different camera modules. This paper describes appearance based object representation for the distributed vision system in Intelligent Space to achieve consistent labeling of all objects. Then, we discuss how to learn the object color appearance model and how to achieve the multi-object tracking under occlusions.

Design of a Multi-Sensor Data Simulator and Development of Data Fusion Algorithm (다중센서자료 시뮬레이터 설계 및 자료융합 알고리듬 개발)

  • Lee, Yong-Jae;Lee, Ja-Seong;Go, Seon-Jun;Song, Jong-Hwa
    • Journal of the Korean Society for Aeronautical & Space Sciences
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    • v.34 no.5
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    • pp.93-100
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    • 2006
  • This paper presents a multi-sensor data simulator and a data fusion algorithm for tracking high dynamic flight target from Radar and Telemetry System. The designed simulator generates time-asynchronous multiple sensor data with different data rates and communication delays. Measurement noises are incorporated by using realistic sensor models. The proposed fusion algorithm is designed by a 21st order distributed Kalman Filter which is based on the PVA model with sensor bias states. A fault detection and correction logics are included in the algorithm for bad data and sensor faults. The designed algorithm is verified by using both simulation data and actual real data.

VTG based Moving Target Tracking Performance Improvement Method using MITL System in a Maritime Environment (해상환경에서 MITL 시스템을 활용한 VTG 기반 기동표적 추적성능 개선 기법)

  • Baek, Inhye;Woo, S.H. Arman
    • Journal of Korea Multimedia Society
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    • v.22 no.3
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    • pp.357-365
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    • 2019
  • In this paper, we suggest the tracking method of moving multi-objects in maritime environments. The image acquisition is conducted using IR(InfraRed) camera sensors on an airborne platform. Under the circumstance of maritime, the qualities of IR images can be significantly degraded due to the clutter influence, which directly gives rise to a tracking loss problem. In order to reduce the effects from the clutters, we introduce a technical approach under Man-In-The-Loop(MITL) system for enhancing the tracking performance. To demonstrate the robustness of the proposed approach based on VTG(Valid Tracking Gate), the simulations are conducted utilizing the airborne IR video sequences: Then, the tracking performances are compared with the existing Kalman Filter tracking techniques.

A Design of Position Tracking System for Moving Targets with Multi-Sensors (다중센서를 이용한 이동표적의 위치추적시스템 설계)

  • Lim, Joong-Soo
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.11 no.1
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    • pp.96-100
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    • 2010
  • In this paper we present a position tracking system that checks the locations of moving targets in real-time. The system confirms that unknown object invades in watch area using 2 infrared sensors and detect the distance from each sensor to object using 4 ultrasonic sensors, and calculate the position of moving object in x-y coordinate. We specially present an algorithm that decide the location of target in case of target is detected in 2 sensors because of radiation beam width of ultrasonic sensor. We established the algorithm to hardware system and tested the system within a laboratory, and confirmed that the designed system tracked an object exactly in real-time.

Particle-motion-tracking Algorithm for the Evaluation of the Multi-physical Properties of Single Nanoparticles (단일 나노입자의 다중 물리량의 평가를 위한 입자 모션 트랙킹 알고리즘)

  • Park, Yeeun;Kang, Geeyoon;Park, Minsu;Noh, Hyowoong;Park, Hongsik
    • Journal of Sensor Science and Technology
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    • v.31 no.3
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    • pp.175-179
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    • 2022
  • The physical properties of biomaterials are important for their isolation and separation from body fluids. In particular, the precise evaluation of the multi-physical properties of single biomolecules is essential in that the correlation between physical and biological properties of specific biomolecule. However, the majority of scientific equipment, can only determine specific-physical properties of single nanoparticles, making the evaluation of the multi-physical properties difficult. The improvement of analytical techniques for the evaluation of multi-physical properties is therefore required in various research fields. In this study, we developed a motion-tracking algorithm to evaluate the multi-physical properties of single-nanoparticles by analyzing their behavior. We observed the Brownian motion and electric-field-induced drift of fluorescent nanoparticles injected in a microfluidic chip with two electrodes using confocal microscopy. The proposed algorithm is able to determine the size of the nanoparticles by i) removing the background noise from images, ii) tracking the motion of nanoparticles using the circular-Hough transform, iii) extracting the mean squared displacement (MSD) of the tracked nanoparticles, and iv) applying the MSD to the Stokes-Einstein equation. We compared the evaluated size of the nanoparticles with the size measured by SEM. We also determined the zeta-potential and surface-charge density of the nanoparticles using the extracted electrophoretic velocity and the Helmholtz-Smoluchowski equation. The proposed motion-tracking algorithm could be employed in various fields related to biomaterial analysis, such as exosome analysis.

Design and Implementation of Intelligent Wireless Sensor Network Based Home Network System (무선 센서 네트워크 기반의 지능형 홈 네트워크 시스템 설계 및 구현)

  • Shin, Jae-Wook;Yoon, Ba-Da;Kim, Sung-Gil;Chung, Wan-Young
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2007.10a
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    • pp.465-468
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    • 2007
  • An intelligent home network system using low-power and low-cost sensor nodes was designed and implemented. In Intelligent Home Network System, active home appliances control is composed of RSSI (Received Signal Strength Indicator) based user indoor location tracking, dynamic multi-hop routing, and learning integration remote-control. Through the remote-control learning, home appliances can be controlled in wireless network environment. User location information for intelligent service is calculated using RSSI based Triangle measurement method, and then the received location information is passed to Smoothing Algorithm to reduce error rate. In order to service Intelligent Home Network, moreover, the sensor node is designed to be held by user. The gathered user data is transmitted through dynamic multi-hop routing to server, and real-time user location & environment information are displayed on monitoring program.

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A Tracking Algorithm for Autonomous Navigation of AGVs: Federated Information Filter

  • Kim, Yong-Shik;Hong, Keum-Shik
    • Journal of Navigation and Port Research
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    • v.28 no.7
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    • pp.635-640
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    • 2004
  • In this paper, a tracking algorithm for autonomous navigation of automated guided vehicles (AGVs) operating in container terminals is presented. The developed navigation algorithm takes the form of a federated information filter used to detect other AGVs and avoid obstacles using fused information from multiple sensors. Being equivalent to the Kalman filter (KF) algebraically, the information filter is extended to N-sensor distributed dynamic systems. In multi-sensor environments, the information-based filter is easier to decentralize, initialize, and fuse than a KF-based filter. It is proved that the information state and the information matrix of the suggested filter, which are weighted in terms of an information sharing factor, are equal to those of a centralized information filter under the regular conditions. Numerical examples using Monte Carlo simulation are provided to compare the centralized information filter and the proposed one.

Multiple Object Tracking with Color-Based Particle Filter for Intelligent Space (공간지능화를 위한 색상기반 파티클 필터를 이용한 다중물체추적)

  • Jin, Tae-Seok;Hashimoto, Hideki
    • The Journal of Korea Robotics Society
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    • v.2 no.1
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    • pp.21-28
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    • 2007
  • The Intelligent Space(ISpace) provides challenging research fields for surveillance, human-computer interfacing, networked camera conferencing, industrial monitoring or service and training applications. ISpace is the space where many intelligent devices, such as computers and sensors, are distributed. According to the cooperation of many intelligent devices, the environment, it is very important that the system knows the location information to offer the useful services. In order to achieve these goals, we present a method for representing, tracking and human following by fusing distributed multiple vision systems in ISpace, with application to pedestrian tracking in a crowd. And the article presents the integration of color distributions into particle filtering. Particle filters provide a robust tracking framework under ambiguity conditions. We propose to track the moving objects by generating hypotheses not in the image plan but on the top-view reconstruction of the scene. Comparative results on real video sequences show the advantage of our method for multi-object tracking. Also, the method is applied to the intelligent environment and its performance is verified by the experiments.

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Global Map Building and Navigation of Mobile Robot Based on Ultrasonic Sensor Data Fusion

  • Kang, Shin-Chul;Jin, Tae-Seok
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.7 no.3
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    • pp.198-204
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    • 2007
  • In mobile robotics, ultrasonic sensors became standard devices for collision avoiding. Moreover, their applicability for map building and navigation has exploited in recent years. In this paper, as the preliminary step for developing a multi-purpose autonomous carrier mobile robot to transport trolleys or heavy goods and serve as robotic nursing assistant in hospital wards. The aim of this paper is to present the use of multi-sensor data fusion such as ultrasonic sensor, IR sensor for mobile robot to navigate, and presents an experimental mobile robot designed to operate autonomously within both indoor and outdoor environments. The global map building based on multi-sensor data fusion is applied for recognition an obstacle free path from a starting position to a known goal region, and simultaneously build a map of straight line segment geometric primitives based on the application of the Hough transform from the actual and noisy sonar data. We will give an explanation for the robot system architecture designed and implemented in this study and a short review of existing techniques, Hough transform, since there exist several recent thorough books and review paper on this paper. Experimental results with a real Pioneer DX2 mobile robot will demonstrate the effectiveness of the discussed methods.