• Title/Summary/Keyword: fast-tracking

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Approaches to Probabilistic Localization and Tracking for Autonomous Mobility Robot in Unknown Environment (미지환경에서 무인이동체의 자율주행을 위한 확률기반 위치 인식과 추적 방법)

  • Jin, Taeseok
    • Journal of the Korean Society of Industry Convergence
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    • v.25 no.3
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    • pp.341-347
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    • 2022
  • This paper presents a comparison result of two simultaneous localization and mapping (SLAM) algorithms for navigation that have been proposed in literature. The performances of Extended Kalman Filter (EKF) SLAM under Gaussian condition, FastSLAM algorithms using Rao-Blackwellised method for particle filtering are compared in terms of accuracy of state estimations for localization of a robot and mapping of its environment. The algorithms were run using the same type of robot on indoor environment. The results show that the Particle filter based FastSLAM has the better performance in terms of accuracy of localization and mapping. The experimental results are discussed and compared.

SMTG 알고리즘을 이용한 랜드마크의 고속정합

  • Seo, Seok-Bae;Kang, Chi-Ho
    • Aerospace Engineering and Technology
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    • v.4 no.2
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    • pp.230-235
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    • 2005
  • As a precedence research for the COMS(Communication, Oceanic, and Meteorological Satellite), this paper proposes the SMTC(Soble Masked Tracking Guideline) algorighm for a fast landmark matching. The experimental results show that proposed algorithm should recude a lot of calculative time.

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Development of Position Information System using GPS and PDA (GPS와 PDA를 이용한 위치정보시스템 개발에 관한 연구)

  • 최병길;홍상기
    • Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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    • 2004.04a
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    • pp.119-124
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    • 2004
  • Tracking correct position information is essential for rescue active in the case of wreck accidents, abscondence and kid napping. Position information system Using GPS and PDA can trace holder's positions exactly and fast, the system can minimize a loss of lives in emergency circumstance. In this study, it is aimed to develop a chasing system to position holders rapidly during distress situation.

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Adaptive controls for non-linear plant using neural network (신경회로망을 이용한 비선형 플랜트의 적응제어)

  • 정대원
    • 제어로봇시스템학회:학술대회논문집
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    • 1997.10a
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    • pp.215-218
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    • 1997
  • A dynamic back-propagation neural network is addressed for adaptive neural control system to approximate non-linear control system rather than static networks. It has the capability to represent the approximation of nonlinear system without mathematical analysis and to carry out the on-line learning algorithm for real time application. The simulated results show fast tracking capability and adaptive response by using dynamic back-propagation neurons.

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SEQUENTIAL EM LEARNING FOR SUBSPACE ANALYSIS

  • Park, Seungjin
    • Proceedings of the IEEK Conference
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    • 2002.07a
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    • pp.698-701
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    • 2002
  • Subspace analysis (which includes PCA) seeks for feature subspace (which corresponds to the eigenspace), given multivariate input data and has been widely used in computer vision and pattern recognition. Typically data space belongs to very high dimension, but only a few principal components need to be extracted. In this paper I present a fast sequential algorithm for subspace analysis or tracking. Useful behavior of the algorithm is confirmed by numerical experiments.

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A New Design Method of Sliding Mode Fuzzy Controller with Robust and fast Performance (강인성과 응답 성능을 고려한 슬라이딩모드 퍼지 제어기 설계에 관한 연구)

  • 박창우;이장욱
    • Proceedings of the IEEK Conference
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    • 1998.10a
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    • pp.425-428
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    • 1998
  • This paper proposes a new fuzzy controller using variable structure control theory. In this paper, after the time-varying fuzzy sliding surface is designed, the fuzzy rules are defined based on the variable structure control theory. This design method makes the fuzzy controller design more structured and can guarantee the stability and robustness of the fuzzy controller and overcome the shortcoming of the variable structure system. Through computer simulation and experiment of nonlinear inverted pendulum system, this thesis demonstrate that system has the robustness against disturbance and modelling error, and the tracking performance of it is improved.

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Stable Tracking Control to a Non-linear Process Via Neural Network Model

  • Zhai, Yujia
    • Journal of the Korea Convergence Society
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    • v.5 no.4
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    • pp.163-169
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    • 2014
  • A stable neural network control scheme for unknown non-linear systems is developed in this paper. While the control variable is optimised to minimize the performance index, convergence of the index is guaranteed asymptotically stable by a Lyapnov control law. The optimization is achieved using a gradient descent searching algorithm and is consequently slow. A fast convergence algorithm using an adaptive learning rate is employed to speed up the convergence. Application of the stable control to a single input single output (SISO) non-linear system is simulated. The satisfactory control performance is obtained.

Clustering based on Dependence Tree in Massive Data Streams

  • Yun, Hong-Won
    • Journal of information and communication convergence engineering
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    • v.6 no.2
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    • pp.182-186
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    • 2008
  • RFID systems generate huge amount of data quickly. The data are associated with the locations and the timestamps and the containment relationships. It is requires to assure efficient queries and updates for product tracking and monitoring. We propose a clustering technique for fast query processing. Our study presents the state charts of temporal event flow and proposes the dependence trees with data association and uses them to cluster the linked events. Our experimental evaluation show the power of proposing clustering technique based on dependence tree.

Exponential Convergence of A Learning Scheme for Unknown Linear Systems

  • Kuc, Tae-yong;Lee, Jin-Soo
    • 제어로봇시스템학회:학술대회논문집
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    • 1992.10b
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    • pp.550-554
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    • 1992
  • In this paper the issue of convergence rate is introduced for a learning control scheme we have developed and applied for tracking of unknown linear systems. A sufficient condition under which the output trajectory converges exponentially fast is obtained using the controllability grammian of controllable linear systems. Under the same condition it is also shown that the learning control input converges exponentially with the same rate as the rate of output convergence. A numerical example with computer simulation results is presented to show the feasibility of the scheme.

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The Fast Intelligent Tracking (F!T) Tube: Feedback Signal Acquisition

  • Lieshout, P.J.G. van;Engelaar, P.J.
    • 한국정보디스플레이학회:학술대회논문집
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    • 2002.08a
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    • pp.351-354
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    • 2002
  • The F!T tube is a new type of CRT without a shadow mask. Correct color reproduction is performed by an electronic system that measures the landing positions of the electron beams and corrects through a dedicated deflection system. This paper describes in detail the position sensor and some of the electronics needed to build a functional control system. The principle has been shown in single- and triple-beam 17" and 32" tubes, of which results are included.

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