• Title/Summary/Keyword: position uncertainty

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Local and Global Information Exchange for Enhancing Object Detection and Tracking

  • Lee, Jin-Seok;Cho, Shung-Han;Oh, Seong-Jun;Hong, Sang-Jin
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.6 no.5
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    • pp.1400-1420
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    • 2012
  • Object detection and tracking using visual sensors is a critical component of surveillance systems, which presents many challenges. This paper addresses the enhancement of object detection and tracking via the combination of multiple visual sensors. The enhancement method we introduce compensates for missed object detection based on the partial detection of objects by multiple visual sensors. When one detects an object or more visual sensors, the detected object's local positions transformed into a global object position. Local and global information exchange allows a missed local object's position to recover. However, the exchange of the information may degrade the detection and tracking performance by incorrectly recovering the local object position, which propagated by false object detection. Furthermore, local object positions corresponding to an identical object can transformed into nonequivalent global object positions because of detection uncertainty such as shadows or other artifacts. We improved the performance by preventing the propagation of false object detection. In addition, we present an evaluation method for the final global object position. The proposed method analyzed and evaluated using case studies.

Robust Estimation of Position and Direction Based on Robot Velocity in the Inner GPS Environment (실내 GPS 환경에서 로봇의 이동속도기반 강인한 위치 및 방향 추정)

  • Kim, Sung-Suk;Kim, Yong-Tae
    • Journal of the Korean Institute of Intelligent Systems
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    • v.20 no.4
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    • pp.497-502
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    • 2010
  • The accurate estimation of position and direction of the mobile robot is essential for preparing precise movement and works in the inner complex environment. In this paper, we propose a robust estimation method of location and direction using the velocity of mobile robot in the inner GPS environment. The estimation using the inner GPS with ultrasonic sensors have to consider with various acoustic noise and sensor errors. We design a robust estimation method using a membership function based on uncertainty of the obtained information and robot velocity. The simulation results of the proposed method show effectiveness in the contaminated environment with position errors.

Stopping Power Ratio Estimation Method Based on Dual-energy Computed Tomography Denoising Images for Proton Radiotherapy Planning (양성자치료계획을 위한 이중에너지 전산화단층촬영 잡음 제거 영상 기반 저지능비 추정 방법)

  • Byungdu Jo
    • Journal of the Korean Society of Radiology
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    • v.17 no.2
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    • pp.207-213
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    • 2023
  • Computed tomography (CT) images are used as the basis for proton Bragg peak position estimation and treatment plan simulation. During the Hounsfield Unit (HU) based proton stopping power ratio (SPR) estimation, small differences in the patient's density and elemental composition lead to uncertainty in the Bragg peak positions along the path of the proton beam. In this study, we investigated the potential of dual-energy computed tomography image-based proton SPRs prediction accuracy to reduce the uncertainty of Bragg peak position prediction. Single- and dual-energy images of an electron density phantom (CIRS Model 062M electron density phantom, CIRS Inc., Norfolk, VA, USA) were acquired using a computed tomography system (Somatom Definition AS, Siemens Health Care, Forchheim, Germany) to estimate the SPRs of the proton beam. To validate the method, it was compared to the SPRs estimated from standard data provided by the National Institute of Standards and Technology (NIST). The results show that the dual-energy image-based method has the potential to improve accuracy in predicting the SPRs of proton beams, and it is expected that further improvements in predicting the position of the proton's Bragg peak will be possible if a wider variety of substitutes with different densities and elemental compositions of the human body are used to predict the SPRs.

Optimal contact force control for a linear magnetostatic actuator (선형 Magnetostatic 작동기의 정밀 접촉력제어를 위한 최적제어기 설계)

  • ;Masada, G.;Busch-Vishniac, I.
    • 제어로봇시스템학회:학술대회논문집
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    • 1997.10a
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    • pp.272-275
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    • 1997
  • When a manipulator makes contact with an object having position uncertainty, performance measures vary considerably with the control law. To achieve the optimal solution for this problem, an unique objective function that weights time and impact force is suggested and is solved with the help of variational calculus. The resulting optimal velocity profile is then modified to define a sliding mode for the impact and force control. The sliding mode control technique is used to achieve the desired performance. Sets of experiments are performed, which show superior performance compared to any existing controller.

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The nonlinear dynamic control of BLDC motors : an adaptive learning control approach (적응 학습 제어 기법을 이용한 BLDC 모터의 비선형 동력학 제어)

  • 박정동;국태용
    • 제어로봇시스템학회:학술대회논문집
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    • 1997.10a
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    • pp.333-336
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    • 1997
  • In this paper, we present a nonlinear dynamic controller for position tracking of brushless dc motors. In constructing the controller, a backstepping-type approach is used under the condition of full state information, while an adaptive controller is adopted for parameter uncertainty throughout the entire electromechanical system. The nonlinear dynamic controller using the adaptive learning technique approach is shown to drive the state variables of system to the desired ones asymptotically and whose effectiveness is also sown via computer simulation.

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A study on approach of localization problem using landmarks (Landmark를 이용한 localization 문제 접근에 관한 연구)

  • 김태우;이쾌희
    • 제어로봇시스템학회:학술대회논문집
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    • 1997.10a
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    • pp.44-47
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    • 1997
  • Building a reliable mobile robot - one that can navigate without failures for long periods of time - requires that the uncertainty which results from control and sensing is bounded. This paper proposes a new mobile robot localization method using artificial landmarks. For a mobile robot localization, the proposed method uses a camera calibration(only extrinsic parameters). We use the FANUC arc mate to estimate the posture error, and the result shows that the position error is less than 1 cm and the orientation error less than 1 degrees.

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Adaptive Robust Control for 2 Aaxis Direct Drive SCARA Robots (2축 직접 구동 SCARA 로봇에 대한 적응 견실제어)

  • 이지형;강철구
    • 제어로봇시스템학회:학술대회논문집
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    • 1993.10a
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    • pp.642-647
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    • 1993
  • In general, systems contain uncertain elements in the real world; these may be parameters, constant or varying, that are unknown or imperfectly known. When the uncertainty is assumed to satisfy the matching condition and to be cone-bounded, Y.H. Chen[81 proposed an adaptive robust control algorithm which introduced adaptive scheme for a design parameter into robust deterministic controls. In this paper, the above control algorithm is applied to the position tracking control of 2 DOF direct drive SCARA robots, and simulation and experimental studies are conducted to verify the control algorithm and to evaluate control performance.

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Lyapunov Stability Analysis of IPD Control for 2nd Order Regulation Servo Systems (2차 레귤레이션 서보 시스템을 위한 IPD 제어의 Lyapunov 안정도 해석)

  • 이정훈
    • Proceedings of the KIPE Conference
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    • 1999.07a
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    • pp.382-385
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    • 1999
  • In this paper, by means of Lyapunov second method, the stability of IPD control servo systems is analyzed in the time domain for the first time. Based on the results of the stability analysis, the design rule to select the gain of IPD control is suggested such that the maximum error of output to the nominal system is guaranteed for all uncertainty and load variations. An example of a position control of a brushless dc motor is given to prove the unusefulness of the gain design rule.

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Adaptive Control of Uncertain Systems without Knowing Perfect Uncertainty Bounds (불확실한 시스템의 적응제어)

  • Kim, Hong-Seok;Choi, Chong-Ho
    • Proceedings of the KIEE Conference
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    • 1989.07a
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    • pp.57-61
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    • 1989
  • An adaptive control scheme is presented for uncertain systems whose uncertaintiy bounds are expressed as a linear combination of unknown functions of special form. Both the states and the parameter estimate errors of the closed-loop system are proven to be bounded. The regulation errors can be made sufficiently small by adjusting the design parameters. An application of the proposed method to the position control of a simple pendulum is given.

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