A PCA-based interpretation of ultrasonic data for accurately detecting a corridor wall

Giannoccaro, Nicola Ivan; Spedicato, Luigi

doi:10.1109/ssd.2012.6197922

Cited by 7 publications

(27 citation statements)

References 10 publications

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“…The PCA consists in an orthogonal transformation in order to analyse the data [10,11]. This method is frequently used in computer vision for image compression.…”

Section: Reconstruction Strategy Based On Cluster Analysis and Pcamentioning

confidence: 99%

Clustering and PCA for Reconstructing Two Perpendicular Planes Using Ultrasonic Sensors

Spedicato

Giannoccaro

Reina

et al. 2013

International Journal of Advanced Robotic Systems

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In this paper, the authors make use of sonar transducers to detect the corner of two orthogonal panels and they propose a strategy for accurately reconstructing the surfaces. In order to point a linear array of four sensors at the desired position, the motion of a digital motor is appropriately controlled. When the sensors are directed towards the intersection between the planes, longer times of flight are observed because of multiple reflections. All the concerned distances have to be excluded and that is why an indicator based on the output signal energy is introduced. A clustering technique allows for the partitioning of the dataset in three clusters and the indicator selects the subset containing misrepresented information. The remaining distances are corrected so as to take into consideration the directivity and they permit the plotting of two sets of points in a three-dimensional space. In order to leave out the outliers, each set is filtered by means of a confidence ellipsoid which is defined by the Principal Component Analysis (PCA). The best-fit planes are obtained based on the principal directions and the variances. Experimental tests and results are shown demonstrating the effectiveness of this new approach.

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“…The PCA consists in an orthogonal transformation in order to analyse the data [10,11]. This method is frequently used in computer vision for image compression.…”

Section: Reconstruction Strategy Based On Cluster Analysis and Pcamentioning

confidence: 99%

Clustering and PCA for Reconstructing Two Perpendicular Planes Using Ultrasonic Sensors

Spedicato

Giannoccaro

Reina

et al. 2013

International Journal of Advanced Robotic Systems

Self Cite

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“…The experimental model refers to the rotation of a sonar sensor that is able to spread a wide ultrasonic beam [11]. The realized mechatronics scanner is depicted in Figure 1.…”

Section: A Model For the Ultrasonic Propagationmentioning

confidence: 99%

“…It may be linked to the equation of a set of ellipses defined by (11), where cij {i,j=1,2} is the generic element of C and C33 is a negative parameter, which has to be fixed in order to draw an ellipse of the set. …”

Section: Pca-based Approach Using the Covariancementioning

confidence: 99%

“…Therefore, a preliminary analysis of the parameter e permits the verification of both the regularity of the wall and the free path for the waves. The eigenvectors associated with the eigenvalues of the matrix C are orthogonal to each other and they describe the direction of the axes of the ellipse defined by (11). If the matrix X is built considering only the data concerned with successful detections (measured distance lower than a threshold [13]), it is very interesting to observe that there is a direct relationship between β and the clockwise rotation angle γ for expressing the ellipse (11) in canonical form with the major axis corresponding to the vertical axis.…”

Section: Pca-based Approach Using the Covariancementioning

confidence: 99%

“…The second technique considers the centre of a Fitting Circumference (FC) for describing the circular arc resulting from a drawing. Finally, the third and most innovative approach is a refinement of the recently introduced method based on the PCA [11]. This last method permits taking advantage of statistical considerations by means of the calculation of a covariance matrix.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Three Different Approaches for Localization in a Corridor Environment by Means of an Ultrasonic Wide Beam

Spedicato

Giannoccaro

Reina

et al. 2013

International Journal of Advanced Robotic Systems

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In this paper the authors present three methods to detect the position and orientation of an observer, such as a mobile robot, with respect to a corridor wall. They use an inexpensive sensor to spread a wide ultrasonic beam. The sensor is rotated by means of an accurate servomotor in order to propagate ultrasonic waves towards a regular wall. Whatever the wall material may be the scanning surface appears to be an acoustic reflector as a consequence of low air impedance. The realized device is able to give distance information in each motor position and thus permits the derivation of a set of points as a ray trace-scanner. The dataset contains points lying on a circular arc and relating to strong returns. Three different approaches are herein considered to estimate both the slope of the wall and its minimum distance from the sensor. Slope and perpendicular distance are the parameters of a target plane, which may be calculated in each observer's position to predict its new location. Experimental tests and simulations are shown and discussed by scanning from different stationary locations. They allow the appreciation of the effectiveness of the proposed approaches.

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Kernel PCA and approximate pre-images to extract the closest ultrasonic arc from the scanning of indoor specular environments

2014

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A PCA-based interpretation of ultrasonic data for accurately detecting a corridor wall

Cited by 7 publications

References 10 publications

Clustering and PCA for Reconstructing Two Perpendicular Planes Using Ultrasonic Sensors

Clustering and PCA for Reconstructing Two Perpendicular Planes Using Ultrasonic Sensors

Three Different Approaches for Localization in a Corridor Environment by Means of an Ultrasonic Wide Beam

Kernel PCA and approximate pre-images to extract the closest ultrasonic arc from the scanning of indoor specular environments

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