Coverage-Mapping Method Based on a Hardware Model for Mobile-Robot Positioning in Intelligent Spaces

Martín-Gorostiza, Ernesto; Meca, Francisco Javier Meca; Galilea, José Luis Lázaro; Martos-Naya, Eduardo; Naranjo, F. B.; Esteban, Óscar

doi:10.1109/tim.2009.2023146

Cited by 18 publications

(12 citation statements)

References 33 publications

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“…This paper discusses a positioning system from the other main group of positioning, which focuses on the accurate spatial location and orientation determination, from a point of view of unmanned indoor vehicles like mobile robots or indoor quadrotors. In this field several different principles are used [4] [6] but the only widely used solution is camera based systems [10] The most advaced camera based systems are the so called motion capture (MOCAP) system, which was originally used in biomechanics and film industry. Nowadays MOCAP systems are also used in research of autonomous vehicles [5].…”

Section: Introductionmentioning

confidence: 99%

Realization of an optical indoor positioning system based on TFT technology

Gozse

Soumelidis

Vanek

2013

2013 European Conference on Mobile Robots

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Abstract-The aim of this paper is to present a novel indoor positioning system which is based on a unique idea. The proposed positioning system provides an alternative to currently existing positioning system. A new idea of optical sensing has been applied that in combination with specific analogue preprocessing and digital signal processing techniques is capable to determine the position and the orientation of objects equipped with special markers. The method is based on moving a pinhole between a marker and the photodiode on the detector. A prototype realization is also outlined, and experimental results are presented to confirm the applicability of the method.

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Section: Introductionmentioning

confidence: 99%

Realization of an optical indoor positioning system based on TFT technology

Gozse

Soumelidis

Vanek

2013

2013 European Conference on Mobile Robots

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“…This work has been developed in the context of a phase-shift measuring system for infrared distance estimation to be applied in indoor mobile robot positioning [18]. Indoor positioning systems rely, in most cases, on certain kind of distance estimation.…”

Section: Contextmentioning

confidence: 99%

SNR Degradation in Undersampled Phase Measurement Systems

Salido-Monzú

Meca

Martín-Gorostiza

et al. 2016

Sensors

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A wide range of measuring applications rely on phase estimation on sinusoidal signals. These systems, where the estimation is mainly implemented in the digital domain, can generally benefit from the use of undersampling to reduce the digitizer and subsequent digital processing requirements. This may be crucial when the application characteristics necessarily imply a simple and inexpensive sensor. However, practical limitations related to the phase stability of the band-pass filter prior digitization establish restrictions to the reduction of noise bandwidth. Due to this, the undersampling intensity is practically defined by noise aliasing, taking into account the amount of signal-to-noise ratio (SNR) reduction caused by it considering the application accuracy requirements. This work analyzes the relationship between undersampling frequency and SNR reduction, conditioned by the stability requirements of the filter that defines the noise bandwidth before digitization. The effect of undersampling is quantified in a practical situation where phase differences are measured by in-phase and quadrature (I/Q) demodulation for an infrared ranging application.

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“…The first method implies that all stationary nodes are active (beacons) and the robot has a rotating receiver [1], [3]- [7]. The second method implies using passive landmarks or reflectors and rotating transmitterreceiver [1], [8], [9]. In the three-node triangulation system, three angles are often measured between the robot heading and the directions to the nodes [10].…”

Section: Introductionmentioning

confidence: 99%

Triangulation-based indoor robot localization using extended FIR/Kalman filtering

Granados-Cruz

Pomarico-Franquiz

Shmaliy

et al. 2014

2014 11th International Conference on Electrical Engineering, Computing Science and Automatic Control (CCE)

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A combined extended finite impulse response (EFIR) and Kalman (EFIR/Kalman) algorithm is proposed for mobile robot localization via triangulation. A distinctive advantage of the EFIR algorithm is that it completely ignores the noise statistics which are typically not well known to the engineer. Instead, it requires an optimal averaging interval of Nopt points. To run this algorithm, several initial Kalman estimates are used for the roughly set noise covariances. We consider a mobile robot travelling on an indoor floorspace and localized via triangulation with three nodes in a view. We show that the EFIR/Kalman filter is more accurate than the extended Kalman filter under the uncertain noise statistics and initial state.

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Coverage-Mapping Method Based on a Hardware Model for Mobile-Robot Positioning in Intelligent Spaces

Cited by 18 publications

References 33 publications

Realization of an optical indoor positioning system based on TFT technology

Realization of an optical indoor positioning system based on TFT technology

SNR Degradation in Undersampled Phase Measurement Systems

Triangulation-based indoor robot localization using extended FIR/Kalman filtering

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