A New Strategy for Spatial Reconstruction of Orthogonal Planes Using a Rotating Array of Ultrasonic Sensors

Abstract

In this paper, the authors present a new strategy for accurately reconstructing an L-shaped obstacle such as some wooden panels opportunely connected so as to form a right angle. The mechatronics scanning system consists of four inexpensive ultrasonic sensors moved in three-dimensional (3-D) space by means of a digital motor. The motor rotation is controlled in order to point the sensor array at the target and to obtain distance measurements for each shaft position. Ultrasonic distance sensors propagate large beams and feel the significant effect of multiple reflections. For the sake of excluding all misrepresented distance values at the intersection of the planes, the proposed approach uses powerful mathematical tools together with a physical indicator based on the reflected signal energy. The Fuzzy C-Means (FCM) classification allows partitioning a data set, and the introduced physical indicator is able to select the specific cluster corresponding to the spurious distances. Each remaining cluster permits to calculate the equation of a plane because it is referred to the distance values deriving from a direct reflection. These distances are then transformed considering the sensors directivity and the direction of reflection so as to obtain two sets of 3-D points. Finally, the reconstruction of each plane is achieved by the RANdom SAmple Consensus (RANSAC) in such a way as to better fit these points. The details of this strategy and the experimental tests are shown, demonstrating the applicability and the good results.

New Methods for Robotic Perception by Using in-Air Sonar Data

“…The sonar sensor array used in all the tests is described in [4][5][6][7][8][9][10][11] and is reproduced here for clarity. It is composed of two types of ultrasonic sensors: the Hagisonic AniBat HG-M40DAI and the HG-M40DNI [12].…”

“…Moreover, they carefully examined the physical phenomenon of multiple reflections in the zone close to the intersection, introducing new reconstruction strategies based on powerful mathematical tools, such as Fuzzy C-Means (FCM) algorithm [4][5][6][7][8][9][10][11], RANdom SAmple Consensus (RANSAC) fitting [4][5][6]9], Principal Component Analysis (PCA) [7][8]9,11] and a function inspired by the Gibbs entropy [10].…”

Clustering and PCA for Reconstructing Two Perpendicular Planes Using Ultrasonic Sensors

“…Let us consider all the points (θg, diθ, W(θ)), where θg is obtained by the indexed position which is the requested address value to define the motor instruction packet [15,19]. The aim of partitioning the cloud of points is pursued by means of the FCM clustering.…”

“…The authors implemented an array of four sensors moved by a digital modular actuator [13] and then utilized it to scan and reconstruct an L-shaped obstacle [14]. After this, they carefully examined the physical phenomenon of multiple reflections in the zone close to the intersection and they introduced a new reconstruction strategy based on the Fuzzy C-Means (FCM) algorithm and on the RANdom SAmple Consensus (RANSAC) fitting [15]. They have brought together the previous analyses and observations in such a way as to define a new procedure in which each best-fit plane is obtained by statistical considerations.…”

Performance Analysis of Phased Array and Frequency Diverse Array Radar Ambiguity Functions

“…Phased array radar system has been widely utilized in many modern communications, radar and navigation systems [1,2,3]. In a standard phased-array antenna, the elements are fed coherently and phase shifters or time-delayers are used to scan the beam to the desired direction in space [4].…”