• Title/Summary/Keyword: Localization algorithm

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Dependence of LOB-based Emitter Localization Performance on Bias of Emitter Location and Sensor Trajectory (신호원 위치의 편향성 및 센서 이동경로에 따른 선형 LSE 알고리즘 기반 신호원 위치 추정 성능)

  • Lee, Joon-Ho;Cho, Seong-Woo;Kim, Min-Cheol;Jin, Yong-Ki;Lee, Chang-Hoon
    • Journal of the Korea Institute of Military Science and Technology
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    • v.12 no.5
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    • pp.585-589
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    • 2009
  • In this paper, passive direction-finding localization of the emitter using noisy line-of-bearing (LOB) measurements is considered. The performance of the LOB-based emitter localization using linear LSE algorithm is given. The Dependence of the performance on bias of emitter location and sensor trajectory is illustrated using the numerical results.

Self-Localization Algorithm for a Mobile Air Cleaner

  • Kim, Young-Baek;Cho, Jin-Hee;Rhee, Sang-Yong
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.9 no.4
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    • pp.321-326
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    • 2009
  • The mobile air cleaner analyzes a distribution of polluted air to purify the air fast, calculates an optimal position and moves the position so that it can remove indoor dust more quickly. At this time, the self-localization is necessary to make the mobile air cleaner move accurately to the calculated position. This paper proposed a self-localization algorithm having high accuracy without complicated calculation and implemented it by combining a ultrasonic sensor and video processing technologies, so that it is suitable for a mobile air cleaner, and as a test result, the mean error of $\pm1cm$ appeared between the actually measured position and the calculated position.

Particle Swarm Optimization based Haptic Localization of Plates with Electrostatic Vibration Actuators

  • Gwanghyun Jo;Tae-Heon Yang;Seong-Yoon Shin
    • Journal of information and communication convergence engineering
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    • v.22 no.2
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    • pp.127-132
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    • 2024
  • Haptic actuators for large display panels play an important role in bridging the gap between the digital and physical world by generating interactive feedback for users. However, the generation of meaningful haptic feedback is challenging for large display panels. There are dead zones with low haptic sensations when a small number of actuators are applied. In contrast, it is important to control the traveling wave generated by the actuators in the presence of multiple actuators. In this study, we propose a particle swarm optimization (PSO)-based algorithm for the haptic localization of plates with electrostatic vibration actuators. We modeled the transverse displacement of a plate under the effect of actuators by employing the Kirchhoff-Love plate theory. In addition, starting with twenty randomly generated particles containing the actuator parameters, we searched for the optimal actuator parameters using a stochastic process to yield localization. The capability of the proposed PSO algorithm is reported and the transverse displacement has a high magnitude only in the targeted region.

An LED SAHP-based Planar Projection PTCDV-hop Location Algorithm

  • Zhang, Yuexia;Chen, Hang;Jin, Jiacheng
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.13 no.9
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    • pp.4541-4554
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    • 2019
  • This paper proposes a planar projection DV-hop location algorithm (PTCDV-hop) based on the LED semi-angle at half power (SAHP, which accounts for LED SAHP characteristics in visible light communication (VLC)) and uses the DV-hop algorithm for range-free localization. Distances between source nodes and nodes positioned in three-dimensional indoor space are projected onto a two-dimensional plane to reduce complexity. Circles are structured by assigning source nodes (projected onto the horizontal plane of the assigned nodes) to be centers and the projection distances as radii. The proposed PTCDV-hop algorithm then determines the position of node location coordinates using the trilateral-weighted-centroid algorithm. Simulation results show localization errors of the proposed algorithm are on the order of magnitude of a millimeter when three sources are used. The PTCDV-hop algorithm has higher positioning accuracy and stronger dominance than the traditional DV-hop algorithm.

Localization with Two Optical Flow Sensors for Small Unmanned Ground Vehicles (두 개의 광류센서를 이용한 소형무인로봇의 위치 추정 기술)

  • Huh, Jinwook;Kang, Sincheon;Hyun, Dongjun
    • Journal of the Korea Institute of Military Science and Technology
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    • v.16 no.2
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    • pp.95-100
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    • 2013
  • Localization is very important for the autonomous navigation of Unmanned Ground Vehicles; however, it is difficult that they have a precise Inertial Navigation System(INS) sensor, especially Small Unmanned Ground Vehicle(SUGV). Moreover, there are some condition such as denial of global position system(GPS), GPS/INS integrated system is not robust. This paper proposes the estimation algorithm with optical flow sensor and INS. Being compared with previous researches, the proposed algorithm is suitable for skid steering vehicles. We revised the measurement model of previous research for the accuracy of side direction position. Experimental results were performed to verify the algorithm, and the result showed an excellent performance.

Robust Localization Algorithm for Mobile Robots in a Dynamic Environment with an Incomplete Map (동적 환경에서 불완전한 지도를 이용한 이동로봇의 강인한 위치인식 알고리즘의 개발)

  • Lee, Jung-Suk;Chung, Wan Kyun;Nam, Sang Yep
    • IEMEK Journal of Embedded Systems and Applications
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    • v.3 no.2
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    • pp.109-118
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    • 2008
  • We present a robust localization algorithm using particle filter for mobile robots in a dynamic environment. It is difficult to describe moving obstacles like people or other robots on the map and the environment is changed after mapping. A mobile robot cannot estimate its pose robustly with this incomplete map because sensor observations are corrupted by un-modeled obstacles. The proposed algorithms provide robustness in such a dynamic environment by suppressing the effect of corrupted sensor observations with a selective update or a sampling from non-corrupted window. A selective update method makes some particles keep track of the robot, not affected by the corrupted observation. In a sampling from non-corrupted window method, particles are always sampled from several particle sets which use only non-corrupted observation. The robustness of proposed algorithm is validated with experiments and simulations.

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Geometry-Based Sensor Selection for Large Wireless Sensor Networks

  • Kim, Yoon Hak
    • Journal of information and communication convergence engineering
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    • v.12 no.1
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    • pp.8-13
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    • 2014
  • We consider the sensor selection problem in large sensor networks where the goal is to find the best set of sensors that maximizes application objectives. Since sensor selection typically involves a large number of sensors, a low complexity should be maintained for practical applications. We propose a geometry-based sensor selection algorithm that utilizes only the information of sensor locations. In particular, by observing that sensors clustered together tend to have redundant information, we theorize that the redundancy is inversely proportional to the distance between sensors and seek to minimize this redundancy by searching for a set of sensors with the maximum average distance. To further reduce the computational complexity, we perform an iterative sequential search without losing optimality. We apply the proposed algorithm to an acoustic sensor network for source localization, and demonstrate using simulations that the proposed algorithm yields significant improvements in the localization performance with respect to the randomly generated sets of sensors.

Localization for Mobile Robot Based on Chirp Spread Spectrum Ranging (Chirp Spread Spectrum거리 측정을 이용한 이동 로봇의 위치 추정)

  • Cho, Hyeon-Woo;Lee, Young-Hun;Kim, Sang-Woo
    • Journal of Institute of Control, Robotics and Systems
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    • v.15 no.10
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    • pp.994-1001
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    • 2009
  • CSS (Chirp Spread Spectrum) specified in IEEE 802.15.4a can be used for ranging applications. In this paper, we apply the CSS to estimate the coordinates of a mobile robot. Four anchor nodes are installed at known positions and a tag node is attached to the target mobile robot. By CSS ranging, we measure the distances between each anchor and the tag node. Based on the measured distances, the coordinates of the mobile robot can be calculated by the method of trilateration. However the calculated coordinates are not accurate because of the errors of the measured distances. Therefore we propose an algorithm for reducing the effect of the errors. The proposed algorithm is executed with the extended Kalman filter. Through localization experiments, we show the performance of the proposed algorithm and the accuracy of the estimated position.

An Improved DV-Hop Algorithm for Scalable Wireless Sensor Network (Scalable 무선 센서 네트워크를 위한 향상된 DV-Hop 알고리즘)

  • Lee, Byeong-Tae;Kim, Sun-Woo
    • Proceedings of the IEEK Conference
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    • 2008.06a
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    • pp.277-278
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    • 2008
  • Localization system is an important problem for Wireless Sensor Networks(WSN). Since the sensor nodes are limited, the range-based that uses the special device for localization is unsuitable in WSN. DV-Hop is one of the range-free localization algorithm using hop-distance and number of hop count. But Its disadvantage is that it spend large communication cost in scalable sensor nodes. We propose a simple algorithm to reduce the communication cost, using the smallest number of hop count.

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Multi-Inernal Division Localization Algorithm by Edge Information for Indoor Wireless Sensor Network (실내 무선 센서 네트워크에서 모서리 정보를 고려한 다중 내분 위치인식 기법)

  • Lee, Ho-Jae;Lee, Sung-Jin;Lee, Sang-Hoon;Kim, Yeon-Soo
    • Proceedings of the IEEK Conference
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    • 2008.06a
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    • pp.363-364
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    • 2008
  • Localization algorithms are required for indoor sensor network applications. In this paper, we introduce an efficient algorithm for low complexity and high accuracy, termed multi-internal division localization(MID), which emphasizes simple refinement and low system-load for low-cost and low-rate wireless sensors. We inspect MID algorithm through MATLAB simulation.

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