Design of a distributed ultrasound-based sensory system

Different sensors may be used for a robot environment analysis: infrared sensors, laser sensors, sonars, RGB and depth cameras. Most of them provide satisfying information about the distance and the shape of observed objects. However, the main drawback of these sensors is the inability to discriminate among different analyzed objects if the latter share the same color, texture or distance. A distributed ultrasound-based sensory system composed from multiple ultrasonic cells is proposed. The system uses a master-slave control architecture. This paper presents the most important part of such system - a low-cost ultrasonic cell with the ability to classify objects by exploiting the magnitude of reflected ultrasonic waves. Traditional ultrasonic sensors only provide information about the distance, but the presented ultrasonic cell also measures the acoustic reflection coefficient of analyzed object. This coefficient allows to differ among materials or objects. Experiments are conducted to demonstrate the performance of the proposed ultrasonic cell.

[1]  Joaquim Salvi,et al.  The SLAM problem: a survey , 2008, CCIA.

[2]  K.D. Champaigne Low-power Electronics for Distributed Impact Detection and Piezoelectric Sensor Applications , 2007, 2007 IEEE Aerospace Conference.

[3]  José Ruíz Ascencio,et al.  Visual simultaneous localization and mapping: a survey , 2012, Artificial Intelligence Review.

[4]  Guang-Zhong Yang,et al.  Simultaneous Stereoscope Localization and Soft-Tissue Mapping for Minimal Invasive Surgery , 2006, MICCAI.

[5]  José-Enrique Simó-Ten,et al.  Using infrared sensors for distance measurement in mobile robots , 2002, Robotics Auton. Syst..

[6]  O. Basset,et al.  Ultrasound Medical Imaging , 2014 .

[7]  Marcin Kowalski,et al.  ULTRASONIC FLOW MEASUREMENT WITH HIGH RESOLUTION , 2014 .

[8]  Thomas L. Szabo,et al.  Causal theories and data for acoustic attenuation obeying a frequency power law , 1995 .

[9]  Robert J. McGough,et al.  Fractional wave equations with attenuation , 2012, Fractional calculus & applied analysis.

[10]  J. M. M. PINKERTON,et al.  Absorption of Ultrasonic Waves in Acetic Acid , 1948, Nature.

[11]  George S. K. Wong,et al.  Speed of sound in standard air , 1986 .

[12]  Dong-Hyun Kim,et al.  3D boiler tube leak detection technique using acoustic emission signals for power plant structure health monitoring , 2011, 2011 Prognostics and System Health Managment Confernece.

[13]  John M. Dolan,et al.  Safe and Efficient Robotic Space Exploration with Tele-Supervised Autonomous Robots , 2006, AAAI Spring Symposium: To Boldly Go Where No Human-Robot Team Has Gone Before.

[14]  Ho Gi Jung,et al.  Scanning Laser Radar-Based Target Position Designation for Parking Aid System , 2008, IEEE Transactions on Intelligent Transportation Systems.

[15]  Lawrence E. Kinsler,et al.  Fundamentals of acoustics , 1950 .

[16]  George Chryssolouris,et al.  On generating the motion of industrial robot manipulators , 2015 .

[17]  Andrei S. Dukhin,et al.  Characterization of Liquids, Nano- And Microparticulates, and Porous Bodies Using Ultrasound , 2010 .

[18]  A. Vladišauskas,et al.  Absorption of ultrasonic waves in air , 2005 .

[19]  M. Caputo Linear Models of Dissipation whose Q is almost Frequency Independent-II , 1967 .

[20]  Zhanjie Song,et al.  Truncation and aliasing errors for Whittaker-Kotelnikov-Shannon sampling expansion , 2012 .

[21]  José Luis Lázaro,et al.  Guidance of a mobile robot using an array of static cameras located in the environment , 2007, Auton. Robots.

[22]  Jie Wang,et al.  A Study of Ultrasonic Flowmeter in Ship Piping Leakage Detection System , 2011, 2011 3rd International Workshop on Intelligent Systems and Applications.