• Title, Summary, Keyword: Localization

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SENSITIVITY OF SHEAR LOCALIZATION ON PRE-LOCALIZATION DEFORMATION MODE

  • Kim, Kwon--Hee-
    • Proceedings of the Korean Society for Technology of Plasticity Conference
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    • pp.83-102
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    • 1992
  • As shear localization is observed in different deformation modes, an attempt is made to understand the conditions for shear localization in general deformation modes. Most emphasis in put upon the effects of pre-localization deformation mode on the onset of shear localization and all the other well-recognized effects of subtle constitutive features and imperfection sensitivity studied elsewhere are not investigated here. Rather, an approximate perturbation stability analysis is performed for simplified isotropic rigid-plastic solids subjected to general mode of homogeneous deformation. Shear localization is possible in any deformation mode if the material has strain softening. The incipient rate of shear localization and shear plane orientations are strongly dependent upon the pre-localization deformation mode. Significant strain softening is necessary for shear localization in homogeneous axisymmetric deformation modes while infinitesimal strain softening is necessary for shear localization in plane strain deformation mode. In any deformation mode, there are more than one shear plane orientation. Except for homogeneous axisymmetric deformation modes, there are two possible shear plane orientations with respect to the principal directions of stretching. Some well-known examples are discussed in the light of the current analysis.

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An Effective TOA-based Localization Method with Adaptive Bias Computation

  • Go, Seung-Ryeol
    • Journal of IKEEE
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    • v.20 no.1
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    • pp.1-8
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    • 2016
  • In this paper, we propose an effective time-of-arrival (TOA)-based localization method with adaptive bias computation in indoor environments. The goal of the localization is to estimate an accurate target's location in wireless localization system. However, in indoor environments, non-line-of-sight (NLOS) errors block the signal propagation between target device and base station. The NLOS errors have significant effects on ranging between two devices for wireless localization. In TOA-based localization, finding the target's location inside the overlapped area in the TOA-circles is difficult. We present an effective localization method using compensated distance with adaptive bias computation. The proposed method is possible for the target's location to estimate an accurate location in the overlapped area using the measured distances with subtracted adaptive bias. Through localization experiments in indoor environments, estimation error is reduced comparing to the conventional localization methods.

Adaptive Wireless Localization Filter Containing NLOS Error Mitigation Function

  • Cho, Seong Yun
    • Journal of Positioning, Navigation, and Timing
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    • v.5 no.1
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    • pp.1-9
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    • 2016
  • Range-based wireless localization system must measure accurate range between a mobile node (MN) and reference nodes. However, non-line-of-sight (NLOS) error caused by the spatial structures disturbs the localization system obtaining the accurate range measurements. Localization methods using the range measurements including NLOS error yield large localization error. But filter-based localization methods can provide comparatively accurate location solution. Motivated by the accuracy of the filter-based localization method, a filter residual-based NLOS error estimation method is presented in this paper. Range measurement-based residual contains NLOS error. By considering this factor with NLOS error properties, NLOS error is mitigated. Also a process noise covariance matrix tuning method is presented to reduce the time-delay estimation error caused by the single dynamic model-based filter when the speed or moving direction of a MN changes, that is the used dynamic model is not fit the current dynamic of a MN. The presented methods are evaluated by simulation allowing direct comparison between different localization methods. The simulation results show that the presented filter is more accurate than the iterative least squares- and extended Kalman filter-based localization methods.

Multi-Objective Optimization for a Reliable Localization Scheme in Wireless Sensor Networks

  • Shahzad, Farrukh;Sheltami, Tarek R.;Shakshuki, Elhadi M.
    • Journal of Communications and Networks
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    • v.18 no.5
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    • pp.796-805
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    • 2016
  • In many wireless sensor network (WSN) applications, the information transmitted by an individual entity or node is of limited use without the knowledge of its location. Research in node localization is mostly geared towards multi-hop range-free localization algorithms to achieve accuracy by minimizing localization errors between the node's actual and estimated position. The existing localization algorithms are focused on improving localization accuracy without considering efficiency in terms of energy costs and algorithm convergence time. In this work, we show that our proposed localization scheme, called DV-maxHop, can achieve good accuracy and efficiency. We formulate the multi-objective optimization functions to minimize localization errors as well as the number of transmission during localization phase. We evaluate the performance of our scheme using extensive simulation on several anisotropic and isotropic topologies. Our scheme can achieve dual objective of accuracy and efficiency for various scenarios. Furthermore, the recently proposed algorithms require random uniform distribution of anchors. We also utilized our proposed scheme to compare and study some practical anchor distribution schemes.

WSN Lifetime Analysis: Intelligent UAV and Arc Selection Algorithm for Energy Conservation in Isolated Wireless Sensor Networks

  • Perumal, P.Shunmuga;Uthariaraj, V.Rhymend;Christo, V.R.Elgin
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.9 no.3
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    • pp.901-920
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    • 2015
  • Wireless Sensor Networks (WSNs) are widely used in geographically isolated applications like military border area monitoring, battle field surveillance, forest fire detection systems, etc. Uninterrupted power supply is not possible in isolated locations and hence sensor nodes live on their own battery power. Localization of sensor nodes in isolated locations is important to identify the location of event for further actions. Existing localization algorithms consume more energy at sensor nodes for computation and communication thereby reduce the lifetime of entire WSNs. Existing approaches also suffer with less localization coverage and localization accuracy. The objective of the proposed work is to increase the lifetime of WSNs while increasing the localization coverage and localization accuracy. A novel intelligent unmanned aerial vehicle anchor node (IUAN) is proposed to reduce the communication cost at sensor nodes during localization. Further, the localization computation cost is reduced at each sensor node by the proposed intelligent arc selection (IAS) algorithm. IUANs construct the location-distance messages (LDMs) for sensor nodes deployed in isolated locations and reach the Control Station (CS). Further, the CS aggregates the LDMs from different IUANs and computes the position of sensor nodes using IAS algorithm. The life time of WSN is analyzed in this paper to prove the efficiency of the proposed localization approach. The proposed localization approach considerably extends the lifetime of WSNs, localization coverage and localization accuracy in isolated environments.

A Received Signal Strength-based Primary User Localization Scheme for Cognitive Radio Sensor Networks Using Underlay Model-based Spectrum Access

  • Lee, Young-Doo;Koo, Insoo
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.8 no.8
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    • pp.2663-2674
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    • 2014
  • For cognitive radio sensor networks (CRSNs) that use underlay-based spectrum access, the location of the primary user (PU) plays an important role in the power control of the secondary users (SUs), because the SUs must keep the minimum interference level required by the PU. Received signal strength (RSS)-based localization schemes provide low-cost implementation and low complexity, thus it is suitable for the PU localization in CRSNs. However, the RSS-based localization schemes have a high localization error because they use an inexact path loss exponent (PLE). Thus, applying a RSS-based localization scheme into the PU localization would cause a high interference to the PU. In order to reduce the localization error and improve the channel reuse rate, we propose a RSS-based PU localization scheme that uses distance calibration for CRSNs using underlay model-based spectrum access. Through the simulation results, it is shown that the proposed scheme can provide less localization error as well as more spectrum utilization than the RSS-based PU localization using the mean and the maximum likelihood calibration.

Probabilistic localization of the service robot by mapmatching algorithm

  • Lee, Dong-Heui;Woojin Chung;Kim, Munsang
    • 제어로봇시스템학회:학술대회논문집
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    • pp.92.3-92
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    • 2002
  • A lot of localization algorithms have been developed in order to achieve autonomous navigation. However, most of localization algorithms are restricted to certain conditions. In this paper, Monte Carlo localization scheme with a map-matching algorithm is suggested as a robust localization method for the Public Service Robot to accomplish its tasks autonomously. Monte Carlo localization can be applied to local, global and kidnapping localization problems. A range image based measure function and a geometric pattern matching measure function are applied for map matching algorithm. This map matching method can be applied to both polygonal environments and un-polygonal environments and achieves...

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Beacon Color Code Scheduling for the Localization of Multiple Robots (다 개체 로봇의 위치인식을 위한 비컨 컬러 코드 스케줄링)

  • Park, Jae-Hyun;Lee, Jang-Myung
    • Journal of Institute of Control, Robotics and Systems
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    • v.16 no.5
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    • pp.433-439
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    • 2010
  • This paper proposes a beacon color code scheduling algorithm for the localization of multiple robots in a multi-block workspace. With the developments of intelligent robotics and ubiquitous technology, service robots are applicable for the wide area such as airports and train stations where multiple indoor GPS systems are required for the localization of the mobile robots. Indoor localization schemes using ultrasonic sensors have been widely studied due to its cheap price and high accuracy. However, ultrasonic sensors have some shortages of short transmission range and interferences with other ultrasonic signals. In order to use multiple robots in wide workspace concurrently, it is necessary to resolve the interference problem among the multiple robots in the localization process. This paper proposes an indoor localization system for concurrent multiple robots localization in a wide service area which is divided into multi-block for the reliable sensor operation. The beacon color code scheduling algorithm is developed to avoid the signal interferences and to achieve efficient localization with high accuracy and short sampling time. The performance of the proposed localization system is verified through the simulations and the real experiments.

Spatially Mapped GCC Function Analysis for Multiple Source and Source Localization Method (공간좌표로 사상된 GCC 함수의 다 음원에 대한 해석과 음원 위치 추정 방법)

  • Kwon, Byoung-Ho;Park, Young-Jin;Park, Youn-Sik
    • Journal of Institute of Control, Robotics and Systems
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    • v.16 no.5
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    • pp.415-419
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    • 2010
  • A variety of methods for sound source localization have been developed and applied to several applications such as noise detection system, surveillance system, teleconference system, robot auditory system and so on. In the previous work, we proposed the sound source localization using the spatially mapped GCC functions based on TDOA for robot auditory system. Performance of the proposed one for the noise effect and estimation resolution was verified with the real environmental experiment under the single source assumption. However, since multi-talker case is general in human-robot interaction, multiple source localization approaches are necessary. In this paper, the proposed localization method under the single source assumption is modified to be suitable for multiple source localization. When there are two sources which are correlated, the spatially mapped GCC function for localization has three peaks at the real source locations and imaginary source location. However if two sources are uncorrelated, that has only two peaks at the real source positions. Using these characteristics, we modify the proposed localization method for the multiple source cases. Experiments with human speeches in the real environment are carried out to evaluate the performance of the proposed method for multiple source localization. In the experiments, mean value of estimation error is about $1.4^{\circ}$ and percentage of multiple source localization is about 62% on average.

Comparison of Edge Localization Performance of Moment-Based Operators Using Target Image Data

  • Seo, Suyoung
    • Korean Journal of Remote Sensing
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    • v.32 no.1
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    • pp.13-24
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    • 2016
  • This paper presents a method to evaluate the performance of subpixel localization operators using target image data. Subpixel localization of edges is important to extract the precise shape of objects from images. In this study, each target image was designed to provide reference lines and edges to which the localization operators can be applied. We selected two types of moment-based operators: Gray-level Moment (GM) operator and Spatial Moment (SM) operator for comparison. The original edge localization operators with kernel size 5 are tested and their extended versions with kernel size 7 are also tested. Target images were collected with varying Camera-to-Object Distance (COD). From the target images, reference lines are estimated and edge profiles along the estimated reference lines are accumulated. Then, evaluation of the performance of edge localization operators was performed by comparing the locations calculated by each operator and by superimposing them on edge profiles. Also, enhancement of edge localization by increasing the kernel size was also quantified. The experimental result shows that the SM operator whose kernel size is 7 provides higher accuracy than other operators implemented in this study.