Building Similarity Maps Of The Environment Using SONAR Information For The Navigation Of The Mobile Robots

The objective of the work is to present a representation called similarity map based on some results in the evaluation of the SONAR system of a mobile robot. As environment a corner of our lab it is considered. Based on some reference positions, where the robot is making a complete rotation, some test positions are considered with the task of recognition of the environment, in order to be able to recognize the position. Using similarity measures based on Euclidian distance, similarities maps are defined and estimated. The results are useful in defining complex strategies of navigation using SONAR systems

Flat surface reconstruction using sonar

Journal ArticleA technique is given for the recovery of planar surfaces using two beam-spread sonar readings. If a single, planar surface gave rise to the two readings, then the method recovers the surface quite accurately. Simulation and experiment demonstrate the effectiveness of the technique and recommend its use in practice

Using a mobile robot to test a theory of cognitive mapping

This paper describes using a mobile robot, equipped with some sonar sensors and an odometer, to test navigation through the use of a cognitive map. The robot explores an office environment, computes a cognitive map, which is a network of ASRs [36, 35], and attempts to find its way home. Ten trials were conducted and the robot found its way home each time. From four random positions in two trials, the robot estimated the home position relative to its current position reasonably accurately. Our robot does not solve the simultaneous localization and mapping problem and the map computed is fuzzy and inaccurate with much of the details missing. In each homeward journey, it computes a new cognitive map of the same part of the environment, as seen from the perspective of the homeward journey. We show how the robot uses distance information from both maps to find its way home. © 2007 Springer-Verlag Berlin Heidelberg

3-Dimensional Sonic Phase-invariant Echo Localization

Parallax and Time-of-Flight (ToF) are often regarded as complementary in robotic vision where various light and weather conditions remain challenges for advanced camera-based 3-Dimensional (3-D) reconstruction. To this end, this paper establishes Parallax among Corresponding Echoes (PaCE) to triangulate acoustic ToF pulses from arbitrary sensor positions in 3-D space for the first time. This is achieved through a novel round-trip reflection model that pinpoints targets at the intersection of ellipsoids, which are spanned by sensor locations and detected arrival times. Inter-channel echo association becomes a crucial prerequisite for target detection and is learned from feature similarity obtained by a stack of Siamese Multi-Layer Perceptrons (MLPs). The PaCE algorithm enables phase-invariant 3-D object localization from only 1 isotropic emitter and at least 3 ToF receivers with relaxed sensor position constraints. Experiments are conducted with airborne ultrasound sensor hardware and back this hypothesis with quantitative results

Location and curvature estimation of 'spherical' targets using a flexible sonar configuration

A novel, flexible, three-dimensional (3-D) multi-sensor sonar system is employed to localize the center of a spherical target and estimate its radius of curvature. The interesting limiting cases for the problem under study are the point and planar targets, both of which are important for the characterization of a mobile robot's environment. A noise model is developed based on real sonar data. An extended Kalman filter (EKF) which incorporates the developed noise model is employed as an estimation tool for optimal processing of the sensor data. Simulations and experimental results are provided for specularly reflecting cylindrical targets

Wall-Corner Classification Using Sonar: A New Approach Based on Geometric Features

Ultrasonic signals coming from rotary sonar sensors in a robot gives us several features about the environment. This enables us to locate and classify the objects in the scenario of the robot. Each object and reflector produces a series of peaks in the amplitude of the signal. The radial and angular position of the sonar sensor gives information about location and their amplitudes offer information about the nature of the surface. Early works showed that the amplitude can be modeled and used to classify objects with very good results at short distances—80% average success in classifying both walls and corners at distances less than 1.5 m. In this paper, a new set of geometric features derived from the amplitude analysis of the echo is presented. These features constitute a set of characteristics that can be used to improve the results of classification at distances from 1.5 m to 4 m. Also, a comparative study on classification algorithms widely used in pattern recognition techniques has been carried out for sensor distances ranging between 0.5 to 4 m, and with incidence angles ranging between 20° to 70°. Experimental results show an enhancement on the success in classification rates when these geometric features are considered

3D indoor positioning of UAVs with spread spectrum ultrasound and time-of-flight cameras

Este trabajo propone el uso de un sistema híbrido de posicionamiento acústico y óptico en interiores para el posicionamiento 3D preciso de los vehículos aéreos no tripulados (UAV). El módulo acústico de este sistema se basa en un esquema de Acceso Múltiple por División de Código de Tiempo (T-CDMA), en el que la emisión secuencial de cinco códigos ultrasónicos de espectro amplio se realiza para calcular la posición horizontal del vehículo siguiendo un procedimiento de multilateración 2D. El módulo óptico se basa en una cámara de Tiempo de Vuelo (TOF) que proporciona una estimación inicial de la altura del vehículo. A continuación se propone un algoritmo recursivo programado en un ordenador externo para refinar la posición estimada. Los resultados experimentales muestran que el sistema propuesto puede aumentar la precisión de un sistema exclusivamente acústico en un 70-80% en términos de error cuadrático medio de posicionamiento.This work proposes the use of a hybrid acoustic and optical indoor positioning system for the accurate 3D positioning of Unmanned Aerial Vehicles (UAVs). The acoustic module of this system is based on a Time-Code Division Multiple Access (T-CDMA) scheme, where the sequential emission of five spread spectrum ultrasonic codes is performed to compute the horizontal vehicle position following a 2D multilateration procedure. The optical module is based on a Time-Of-Flight (TOF) camera that provides an initial estimation for the vehicle height. A recursive algorithm programmed on an external computer is then proposed to refine the estimated position. Experimental results show that the proposed system can increase the accuracy of a solely acoustic system by 70–80% in terms of positioning mean square error.• Gobierno de España y Fondos para el Desarrollo Regional Europeo. Proyectos TARSIUS (TIN2015-71564-C4-4-R) (I+D+i), REPNIN (TEC2015-71426-REDT) y SOC-PLC (TEC2015-64835-C3-2-R) (I+D+i) • Junta de Extremadura, Fondos FEDER y Fondo Social Europeo. Proyecto GR15167 y beca predoctoral 45/2016 Exp. PD16030peerReviewe

Accurate estimation of airborne ultrasonic time-of-flight for overlapping echoes

In this work, an analysis of the transmission of ultrasonic signals generated by piezoelectric sensors for air applications is presented. Based on this analysis, an ultrasonic response model is obtained for its application to the recognition of objects and structured environments for navigation by autonomous mobile robots. This model enables the analysis of the ultrasonic response that is generated using a pair of sensors in transmitter-receiver configuration using the pulse-echo technique. This is very interesting for recognizing surfaces that simultaneously generate a multiple echo response. This model takes into account the effect of the radiation pattern, the resonant frequency of the sensor, the number of cycles of the excitation pulse, the dynamics of the sensor and the attenuation with distance in the medium. This model has been developed, programmed and verified through a battery of experimental tests. Using this model a new procedure for obtaining accurate time of flight is proposed. This new method is compared with traditional ones, such as threshold or correlation, to highlight its advantages and drawbacks. Finally the advantages of this method are demonstrated for calculating multiple times of flight when the echo is formed by several overlapping echoes.This work has been supported by the Spanish Government projects DPI2006-15313 and DPI2012-36959

Comparison of two methods for fusing information from a linear array of sonar sensors for obstacle localization

The performance of a commonly employed linear array of sonar sensors is assessed for point-obstacle localization intended for robotics applications. Two different methods of combining time-of-flight information from the sensors are described to estimate the range and azimuth of the obstacle: pairwise estimate method and the maximum likelihood estimator. The variances of the methods are compared to the Cramer-Rao Lower Bound, and their biases are investigated. Simulation studies indicate that in estimating range, both methods perform comparably; in estimating azimuth, maximum likelihood estimate is superior at a cost of extra computation. The results are useful for target localization in mobile robotics

Modeling the Behavior of an Underwater Acoustic Relative Positioning System Based on Complementary Set of Sequences

The great variability usually found in underwater media makes modeling a challenging task, but helpful for better understanding or predicting the performance of future deployed systems. In this work, an underwater acoustic propagation model is presented. This model obtains the multipath structure by means of the ray tracing technique. Using this model, the behavior of a relative positioning system is presented. One of the main advantages of relative positioning systems is that only the distances between all the buoys are needed to obtain their positions. In order to obtain the distances, the propagation times of acoustic signals coded by Complementary Set of Sequences (CSS) are used. In this case, the arrival instants are obtained by means of correlation processes. The distances are then used to obtain the position of the buoys by means of the Multidimensional Scaling Technique (MDS). As an early example of an application using this relative positioning system, a tracking of the position of the buoys at different times is performed. With this tracking, the surface current of a particular region could be studied. The performance of the system is evaluated in terms of the distance from the real position to the estimated one