Data fusion of four ABS sensors and GPS for an enhanced localization of car-like vehicles

Bonnifait, Philippe; Bouron, P.; Crubillé, P.; Meizel, Dominique

doi:10.1109/robot.2001.932839

Cited by 74 publications

(55 citation statements)

References 6 publications

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“…한정된 공 간의 실내 환경에서 원활하게 작업을 수행하는 전제 조건 중 하나가 이동로봇의 정확한 위치와 방향 추정이다. 위치 추정 방법은 비전 시스템을 이용하는 방법에서부터 GPS, 소나, 레이저 거리 스캐너, iGPS까지 여러 가지 방법을 활 용할 수 있으며, 정확도를 높이기 위해 다른 추정 시스템을 융합하는 시도들도 이루어져 왔다 [1][2][3][4][5]. 그러나 각각의 추 정 시스템은 센서 특성과 외부 요인들로 인해 추정된 위치 에는 항상 오차가 존재한다.…”

Section: 서 론unclassified

Robust Estimation of Position and Direction Based on Robot Velocity in the Inner GPS Environment

Kim¹,

Kim²

2010

Journal of Korean Institute of Intelligent Systems

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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.

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Section: 서 론unclassified

Robust Estimation of Position and Direction Based on Robot Velocity in the Inner GPS Environment

Kim¹,

Kim²

2010

Journal of Korean Institute of Intelligent Systems

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“…The system (26) is controllable if u 1 is a piecewise continuous, bounded and strictly positive (or negative) function, as stated in [14]. Therefore, u 2 is the only input to the system as long has u 1 is known a priori: 4 (27) The complete deducing of the controller and its background theory are described in [14].…”

Section: Chained-form-based Lateral Controllermentioning

confidence: 99%

“…So, it is required to complement odometric data with absolute positioning. Data fusion of ABS sensors and GPS for outdoor localization, based on an Extended Kalman Filter (EKF) had been presented in [4]. Selflocalization, given a map of the environment, and the more challenging problem of simultaneous localization and mapping are two examples of key mobile robot problems requiring positioning data.…”

Section: Introductionmentioning

confidence: 99%

Data fusion and path-following controllers comparison for autonomous vehicles

Nunes

Bento

2007

Nonlinear Dyn

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This paper presents a comparative study of two path-following controllers developed for guiding autonomous vehicles in semi-structured outdoor environments. Part of this paper is focused on the performance of two path-following controllers, which are implemented using two different approaches, the first using fuzzy logic and the second using chained systems theory. The control effort and the errors magnitude along the path are evaluated in a comparative way. A magnetic guidance system for autonomous vehicles navigation in semi-structured outdoor environments is also described, integrating redundant encoders data and absolute positioning data provided by onboard magnetic sensors and magnetic markers buried in the road. Simulation and experimental results are presented showing the effectiveness of the overall control system. U. Nunes ( )

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“…The vehicle must be equipped with external sensors that obtain information from the environment to help the vehicle determine its location more accurately. Most researchers utilized GPS, ultrasonic [1][2][3] , optical flow sensor or machine vision based systems to provide the positioning information. The precision or reliability of results can be improved with several sensors [4][5][6][7] .…”

Section: Introductionmentioning

confidence: 99%

Improved Intelligent Vehicle Localization Using Magnetic Ruler

Wang¹,

Yang²,

Wang³

et al. 2011

IJCIS

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This paper proposes an improved intelligent vehicle localization method, which integrates the data from the odometry and the magnetic ruler(MR). The MR is used to detect the magnetic markers, which provides the absolute positioning reference. The data from odometry and the MR are used to localize the vehicle by using unscented Kalman filter. The data association (DA) method is adopted to validate the observations from the MR. The experiment results show that the method is a robust way.

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Data fusion of four ABS sensors and GPS for an enhanced localization of car-like vehicles

Cited by 74 publications

References 6 publications

Robust Estimation of Position and Direction Based on Robot Velocity in the Inner GPS Environment

Robust Estimation of Position and Direction Based on Robot Velocity in the Inner GPS Environment

Data fusion and path-following controllers comparison for autonomous vehicles

Improved Intelligent Vehicle Localization Using Magnetic Ruler

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