Surface Profile Determination from Multiple Sonar Data Using Morphological Processing

Başkent, Deniz; Barshan, Billur

doi:10.1177/02783649922066565

Cited by 35 publications

(28 citation statements)

References 37 publications

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“…Targets that have spatially varying curvature which may become both concave and convex have also been addressed in recent work. 45,46 Naturally, the larger the number of parameters ͑or degrees of freedom͒ of the surface, the larger the number of sensors needed.…”

Section: Discussionmentioning

confidence: 99%

Radius of curvature estimation and localization of targets using multiple sonar sensors

Barshan

Sekmen

1999

The Journal of the Acoustical Society of America

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Acoustic sensors have been widely used in time-of-flight ranging systems since they are inexpensive and convenient to use. One of the most important limitations of these sensors is their low angular resolution. To improve the angular resolution and the accuracy, a novel, flexible, and adaptive three-dimensional ͑3-D͒ multi-sensor sonar system is described for estimating the radius of curvature and location of cylindrical and spherical targets. Point, line, and planar targets are included as limiting cases which are important for the characterization of typical environments. Sensitivity analysis of the curvature estimate with respect to measurement errors and certain system parameters is provided. The analysis and the simulations are verified by experiments in 2-D with specularly reflecting cylindrical and planar targets, using a real sonar system. Typical accuracies in range and azimuth are 0.18 mm and 0.1°, respectively. Accuracy of the curvature estimation depends on the target type and system parameters such as transducer separation and operating range. The adaptive configuration brings an improvement varying between 35% and 45% in the accuracy of the curvature estimate. The presented results are useful for target differentiation and tracking applications.

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Section: Discussionmentioning

confidence: 99%

Radius of curvature estimation and localization of targets using multiple sonar sensors

Barshan

Sekmen

1999

The Journal of the Acoustical Society of America

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“…The real refl ection points are usually "touched" by several arcs and those that cross each of them reinforce the point on the map where an obstacle is really located. Some UAM techniques are spatial voting (Barshan B. , 1999), morphological processing (Baskent & Barshan, 1999), triangulation based fusion (Wijk & Christensen, 2000), arc-transversal median (Choset , Nagatani, & Lazar, 2003) and directional maximum (Barshan B., 2007).…”

Section: Uammentioning

confidence: 99%

Detection and location of surfaces in a 3D environment through a single transducer and ultrasonic spherical caps

Ortiz¹,

Castillo-Castañeda

Zavala

2017

Ing. Inv.

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Detección y localización de superficies en un ambiente 3D a través de un solo sensor y casquetes esféricos ultrasónicosFabio T Moreno-Ortiz 1 , Eduardo Castillo-Castañeda 2 , and Antonio Hernández-Zavala 3 ABSTRACTIn this paper, an ultrasonic arc map method for flat mapping is extended to three-dimensional space replacing the circumference arcs by spherical caps. An enclosed environment is scanned by employing a single ultrasonic device. The range, position, and orientation of the transducer are used to digitize the uncertainty caps and place them in a three-dimensional map. Through the spatial voting method, the generated voxels are elected in order to distinguish those which mark the true position of an obstacle and discard those that are produced by cross talk, noise, fake ranges, and angular resolution. The results show that it is possible to obtain sufficient information to build a three-dimensional map for navigation by employing inexpensive sensors and a low power data processing.Keywords: Ultrasonic arc map, sonar resolution, SLAM, Bresenham algorithm, voxelized spherical cap, beam pattern, spatial voting. RESUMENEn este artículo, un método de mapa de arcos ultrasónicos para mapeo plano es extendido al espacio tridimensional, remplazando los arcos de circunferencia por casquetes esféricos. Un ambiente cerrado es explorado empleando solo un dispositivo ultrasónico. La distancia, posición y orientación del transductor son utilizadas para digitalizar casquetes de incertidumbre y colocarlos en un mapa tridimensional. A través del método de votación espacial, los voxeles generados son elegidos con el propósito de distinguir aquellos que marcan la posición real de un obstáculo y descartar aquellos producidos por diafonía, ruido, lecturas falsas y la resolución angular. Los resultados muestran que es posible obtener suficiente información para construir un mapa tridimensional para navegación mediante el empleo de sensores de bajo costo y un procesamiento de datos de baja potencia.Palabras clave: Mapa de arco ultrasónico, resolución del sonar, SLAM, algoritmo de Bresenham, casquete esférico voxelizado, patrón de dispersión, votación espacial.

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“…The processing of UAMs using morphological operators was first proposed in [6]. This approach exploits neighboring relationships and provides an easy to implement yet effective solution to ultrasonic map building.…”

Section: Morphological Processing (Mp)mentioning

confidence: 99%

“…RCDs are circular arcs which are natural features of the raw ultrasonic TOF data from specularly reflecting surfaces, first reported in [16], and further elaborated on in [9]. Alternatively, the angular uncertainty in the range measurements has been represented by ultrasonic arc maps (UAMs) [6] that preserve more information (see Fig.1(c) for a sample UAM). This is done by drawing arcs spanning the beamwidth of the sensor at the measured range, representing the angular uncertainty of the object location and indicating that the echo-producing object can lie anywhere on the arc.…”

Section: Introductionmentioning

confidence: 99%

“…Basically, active snake curves will be fitted to the results of processing the UAM by each technique and a comparison with a very accurate laser map (considered as absolute reference) will be provided. [16] 5 Bayesian update (BU) [1] 2 Voting and thresholding (VT) [3] 6 Triangle based fusion (TBF) [15] 3 Directional maximum (DM) [4] 7 Arc transversal median (ATM-org) [8] 4 Morphological processing (MP) [6] 8 Modified ATM (ATM-mod) [4] …”

Section: Introductionmentioning

confidence: 99%

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Performance Evaluation of Ultrasonic Arc Map Processing Techniques by Active Snake Contours

Altun

Barshan

Springer Tracts in Advanced Robotics

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Summary. Active snake contours are considered for representing the maps of an environment obtained by different ultrasonic arc map (UAM) processing techniques efficiently. The mapping results are compared with the actual map of the room obtained with a very accurate laser system. This technique is a convenient way to represent and compare the map points obtained with different techniques among themselves, as well as with an absolute reference. It is also applicable to map points obtained with other mapping techniques.

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Surface Profile Determination from Multiple Sonar Data Using Morphological Processing

Abstract: Abstract

Cited by 35 publications

References 37 publications

Radius of curvature estimation and localization of targets using multiple sonar sensors

Radius of curvature estimation and localization of targets using multiple sonar sensors

Detection and location of surfaces in a 3D environment through a single transducer and ultrasonic spherical caps

Performance Evaluation of Ultrasonic Arc Map Processing Techniques by Active Snake Contours

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