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Sonar Sensing

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Springer Handbook of Robotics

Abstract

Sonar or ultrasonic sensing uses the propagation of acoustic energy at higher frequencies than normal hearing to extract information from the environment. This chapter presents the fundamentals and physics of sonar sensing for object localization, landmark measurement and classification in robotics applications. The source of sonar artifacts is explained and how they can be dealt with. Different ultrasonic transducer technologies are outlined with their main characteristics highlighted.

Sonar systems are described that range in sophistication from low-cost threshold-based ranging modules to multitransducer multipulse configurations with associated signal processing requirements capable of accurate range and bearing measurement, interference rejection, motion compensation, and target classification. Continuous-transmission frequency-modulated (CTFM) systems are introduced and their ability to improve target sensitivity in the presence of noise is discussed. Various sonar ring designs that provide rapid surrounding environmental coverage are described in conjunction with mapping results. Finally the chapter ends with a discussion of biomimetic sonar, which draws inspiration from animals such as bats and dolphins.

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Abbreviations

CTFM:

continuous-transmission frequency-modulated

DFT:

discrete Fourier transform

HMM:

hidden Markov model

IAD:

intelligent assist device

ITD:

interaural time difference

MEMS:

microelectromechanical systems

MLE:

maximum-likelihood estimation

MR:

magnetorheological

MR:

multiple reflection

MR:

multirobot tasks

PAS:

pseudo-amplitude scan

PVDF:

polyvinyledene fluoride

SLAM:

simultaneous localization and mapping

TOF:

time of flight

VO:

velocity obstacles

References

  1. L.E. Kinsler, A.R. Frey, A.B. Coppens, J.V. Sanders: Fundamentals of Acoustics (Wiley, New York 1982)

    Google Scholar 

  2. R.C. Weast, M.J. Astle (Eds.): CRC Handbook of Chemistry and Physics, 59th edn. (CRC, Boca Raton 1978)

    Google Scholar 

  3. J. Borenstein, H.R. Everett, L. Feng: Navigating Mobile Robots (Peters, Wellesley 1996)

    MATH  Google Scholar 

  4. R. Kuc, M.W. Siegel: Physically-based simulation model for acoustic sensor robot navigation, IEEE Trans. Pattern Anal. Mach. Intell. 9(6), 766–778 (1987)

    Article  Google Scholar 

  5. SensComp: 7000 Series (SensComp, Livonia 2007), http://www.senscomp.com

    Google Scholar 

  6. H.H. Poole: Fundamentals of Robotics Engineering (Van Nostrand, New York 1989)

    Google Scholar 

  7. J.E. Piercy: American National Standard: Method for Calculation of the Absorption of Sound by the Atmosphere ANSI SI-26-1978 (Acoust. Soc. Am., Washington 1978)

    Google Scholar 

  8. B. Barshan, R. Kuc: A bat-like sonar system for obstacle localization, IEEE Trans. Syst. Man Cybern. 22(4), 636–646 (1992)

    Article  Google Scholar 

  9. R. Kuc: Three dimensional docking using qualitative sonar. In: Intelligent Autonomous Systems IAS-3, ed. by F.C.A. Groen, S. Hirose, C.E. Thorpe (IOS, Washington 1993) pp. 480–488

    Google Scholar 

  10. R. Kuc: Biomimetic sonar locates and recognizes objects, J. Ocean. Eng. 22(4), 616–624 (1997)

    Article  Google Scholar 

  11. L. Kleeman, R. Kuc: Mobile robot sonar for target localization and classification, Int. J. Robot. Res. 14(4), 295–318 (1995)

    Article  Google Scholar 

  12. B. Stanley: A comparison of binaural ultrasonic sensing systems. Ph.D. Thesis (University of Wollongong, Wollongong 2003), http://adt.caul.edu.au/

  13. F.L. Degertekin, S. Calmes, B.T. Khuri-Yakub, X. Jin, I. Ladabaum: Fabrication and characterization of surface micromachined capacitive ultrasonic immersion transducers, J. Microelectromech. Syst. 8(1), 100–114 (1999)

    Article  Google Scholar 

  14. B. Barshan, R. Kuc: Differentiating sonar reflections from corners and planes by employing an intelligent sensor, IEEE Trans. Pattern Anal. Mach. Intell. 12(6), 560–569 (1990)

    Article  Google Scholar 

  15. A. Freedman: A mechanism of acoustic echo formation, Acustica 12, 10–21 (1962)

    MATH  MathSciNet  Google Scholar 

  16. A. Freedman: The high frequency echo structure of somae simple body shapes, Acustica 12, 61–70 (1962)

    MATH  Google Scholar 

  17. Ö. Bozma, R. Kuc: A physical model-based analysis of heterogeneous environments using sonar – ENDURA method, IEEE Trans. Pattern Anal. Mach. Intell. 16(5), 497–506 (1994)

    Article  Google Scholar 

  18. Ö. Bozma, R. Kuc: Characterizing pulses reflected from rough surfaces using ultrasound, J. Acoust. Soc. Am. 89(6), 2519–2531 (1991)

    Article  Google Scholar 

  19. P.J. McKerrow: Echolocation – from range to outline segments. In: Intelligent Autonomous Systems IAS-3, ed. by F.C.A. Groen, S. Hirose, C.E. Thorpe (IOS, Washington 1993) pp. 238–247

    Google Scholar 

  20. J. Thomas, C. Moss, M. Vater (Eds.): Echolocation in Bats and Dolphins (University of Chicago Press, Chicago 2004)

    Google Scholar 

  21. J. Borenstein, Y. Koren: Error eliminating rapid ultrasonic firing for mobile robot obstacle avoidance, IEEE Trans. Robot. Autom. 11(1), 132–138 (1995)

    Article  Google Scholar 

  22. L. Kleeman: Fast and accurate sonar trackers using double pulse coding, Proc. IEEE/RSJ Int. Conf. Intell. Robot. Syst. (1999) pp. 1185–1190

    Google Scholar 

  23. R. Kuc: Pseudo-amplitude sonar maps, IEEE Trans. Robot. Autom. 17(5), 767–770 (2001)

    Article  Google Scholar 

  24. H. Peremans, K. Audenaert, J.M. Van Campenhout: A high-resolution sensor based on tri-aural perception, IEEE Trans. Robot. Autom. 9(1), 36–48 (1993)

    Article  Google Scholar 

  25. A. Sabatini, O. Di Benedetto: Towards a robust methodology for mobile robot localization using sonar, IEEE Int. Conf. Robot. Autom. (1994) pp. 3136–3141

    Google Scholar 

  26. L. Kleeman: Advanced sonar with velocity compenstation, Int. J. Robot. Res. 23(2), 111–126 (2004)

    Article  Google Scholar 

  27. A. Elfes: Sonar-based real world mapping and navigation, IEEE Trans. Robot. Autom. 3, 249–265 (1987)

    Article  Google Scholar 

  28. S. Thrun, M. Bennewitz, W. Burgard, A.B. Cremers, F. Dellaert, D. Fox, D. Haehnel, C. Rosenberg, N. Roy, J. Schulte, D. Schulz: MINERVA: A second geration mobile tour-guide robot, IEEE Int. Conf. Robot. Autom. (1999) pp. 3136–3141

    Google Scholar 

  29. K. Konolige: Improved occupancy grids for map building, Auton. Robot. 4, 351–367 (1997)

    Article  Google Scholar 

  30. R. Grabowski, P. Khosla, H. Choset: An enhanced occupancy map for exploration via pose separation, Proc. IEEE/RSJ Int. Conf. Intell. Robot. Syst. (2003) pp. 705–710

    Google Scholar 

  31. J.D. Tardos, J. Neira, P.M. Newman, J.J. Leonard: Robust mapping and localization in indoor environments using sonar data, Int. J. Robot. Res. 21(6), 311–330 (2002)

    Article  Google Scholar 

  32. O. Aycard, P. Larouche, F. Charpillet: Mobile robot localization in dynamic environments using places recognition, Proc. IEEE Int. Conf. Robot. Autom. (1998) pp. 3135–3140

    Google Scholar 

  33. B. Kuipers, P. Beeson: Bootstrap learning for place recognition, Proc. 18-th Nat. Conf. Artif. Intell. (AAAI-02) (2002)

    Google Scholar 

  34. A. Bandera, C. Urdiales, F. Sandoval: Autonomous global localization using Markov chains and optimized sonar landmarks, Proc. IEEE/RSJ Int. Conf. Intell. Robot. Syst. (2000) pp. 288–293

    Google Scholar 

  35. R. Kuc: Biomimetic sonar and neuromorphic processing eliminate reverberation artifacts, IEEE Sens. J. 7(3), 361–369 (2007)

    Article  Google Scholar 

  36. A.M. Sabatini: A stochastic model of the time-of-flight noise in airborne sonar ranging systems, IEEE Trans. Ultrason. Ferroelectr. Freq. Control 44(3), 606–614 (1997)

    Article  Google Scholar 

  37. C. Biber, S. Ellin, E. Sheck, J. Stempeck: The Polaroid ultrasonic ranging system, Proc. 67th Audio Eng. Soc. Convention (1990)

    Google Scholar 

  38. R. Kuc: Forward model for sonar maps produced with the Polaroid ranging module, IEEE Trans. Robot. Autom. 19(2), 358–362 (2003)

    Article  Google Scholar 

  39. M.K. Brown: Feature extraction techniques for recognizing solid objects with an ultrasonic range sensor, IEEE J. Robot. Autom. RA-1(4), 191–205 (1985)

    Article  Google Scholar 

  40. N.L. Harper, P.J. McKerrow: Classification of plant species from CTFM ultrasonic range data using a neural network, Proc. IEEE Int. Conf. Neural Netw. (1995) pp. 2348–2352

    Google Scholar 

  41. Z. Politis, P.J. Probert: Target localization and identification using CTFM sonar imaging: The AURBIT method, Proc. IEEE Int. Symp. CIRA (1999) pp. 256–261

    Google Scholar 

  42. R. Mueller, R. Kuc: Foliage echoes: A probe into the ecological acoustics of bat echolocation, J. Acoust. Soc. Am. 108(2), 836–845 (2000)

    Article  Google Scholar 

  43. P.N.T. Wells: Biomedical Ultrasonics (Academic, New York 1977)

    Google Scholar 

  44. J.L. Prince, J.M. Links: Medical Imaging Signals and Systems (Pearson Prentice Hall, Upper Saddle River 2006)

    Google Scholar 

  45. J.J. Leonard, H.F. Durrant-Whyte: Mobile robot localization by tracking geometric beacons, IEEE Trans. Robot. Autom. 7(3), 376–382 (1991)

    Article  Google Scholar 

  46. P.M. Woodward: Probability and Information Theory with Applications to Radar, 2nd edn. (Pergamon, Oxford 1964)

    MATH  Google Scholar 

  47. A. Heale, L. Kleeman: Fast target classification using sonar, IEEE/RSJ Int. Conf. Robot. Syst. (2001) pp. 1446–1451

    Google Scholar 

  48. S. Fazli, L. Kleeman: A real time advanced sonar ring with simultaneous firing, Proc. IEEE/RSJ Intern. Conf. Intell. Robot. Syst. (2004) pp. 1872–1877

    Google Scholar 

  49. T. Yata, A. Ohya, S. Yuta: A fast and accurate sonar-ring sensor for a mobile robot, Proc. IEEE Int. Conf. Robot. Autom. (1999) pp. 630–636

    Google Scholar 

  50. L. Kleeman: Scanned monocular sonar and the doorway problem, Proc. IEEE/RSJ Int. Conf. Intell. Robot. Syst. (1996) pp. 96–103

    Google Scholar 

  51. G. Kao, P. Probert: Feature extraction from a broadband sonar sensor for mapping structured environments efficiently, Int. J. Robot. Res. 19(10), 895–913 (2000)

    Article  Google Scholar 

  52. B. Stanley, P. McKerrow: Measuring range and bearing with a binaural ultrasonic sensor, IEEE/RSJ Int. Conf. Intell. Robot. Syst. (1997) pp. 565–571

    Google Scholar 

  53. P.T. Gough, A. de Roos, M.J. Cusdin: Continuous transmission FM sonar with one octave bandwidth and no blind time. In: Autonomous Robot Vehicles, ed. by I.J. Cox, G.T. Wilfong (Springer-Verlag, Berlin, Heidelberg 1990) pp. 117–122

    Google Scholar 

  54. L. Kay: A CTFM acoustic spatial sensing technology: its use by blind persons and robots, Sens. Rev. 19(3), 195–201 (1999)

    Article  MathSciNet  Google Scholar 

  55. L. Kay: Auditory perception and its relation to ultrasonic blind guidance aids, J. Br. Inst. Radio Eng. 24, 309–319 (1962)

    Google Scholar 

  56. P.J. McKerrow, N.L. Harper: Recognizing leafy plants with in-air sonar, IEEE Sens. 1(4), 245–255 (2001)

    Article  Google Scholar 

  57. K. Audenaert, H. Peremans, Y. Kawahara, J. Van Campenhout: Accurate ranging of multiple objects using ultrasonic sensors, Proc. IEEE Int. Conf. Robot. Autom. (1992) pp. 1733–1738

    Google Scholar 

  58. J. Borenstein, Y. Koren: Noise rejection for ultrasonic sensors in mobile robot applications, Proc. IEEE Int. Conf. Robot. Autom. (1992) pp. 1727–1732

    Google Scholar 

  59. K.W. Jorg, M. Berg: Mobile robot sonar sensing with pseudo-random codes, Proc. IEEE Int. Conf. Robot. Autom. (1998) pp. 2807–2812

    Google Scholar 

  60. S. Shoval, J. Borenstein: Using coded signals to benefit from ultrasonic sensor crosstalk in mobile robot obstacle avoidance, Proc. IEEE Int. Conf. Robot. Autom. (2001) pp. 2879–2884

    Google Scholar 

  61. K. Nakahira, T. Kodama, T. Furuhashi, H. Maeda: Design of digital polarity correlators in a multiple-user sonar ranging system, IEEE Trans. Instrum. Meas. 54(1), 305–310 (2005)

    Article  Google Scholar 

  62. A. Heale, L. Kleeman: A sonar sensor with random double pulse coding, Aust. Conf. Robot. Autom. (2000) pp. 81–86

    Google Scholar 

  63. A. Diosi, G. Taylor, L. Kleeman: Interactive SLAM using Laser and Advanced Sonar, Proc. IEEE Int. Conf. Robot. Autom. (2005) pp. 1115–1120

    Google Scholar 

  64. S.A. Walter: The sonar ring: obstacle detection for a mobile robot, Proc. IEEE Int. Conf. Robot. Autom. (1987) pp. 1574–1578

    Google Scholar 

  65. S. Fazli, L. Kleeman: Wall following and obstacle avoidance results from a multi-DSP sonar ring on a mobile robot, Proc. IEEE Int. Conf. Mechatron. Autom. (2005) pp. 432–436

    Google Scholar 

  66. S. Fazli, L. Kleeman: Sensor design and signal processing for an advanced sonar ring, Robotica 24(4), 433–446 (2006)

    Article  Google Scholar 

  67. W.W.L. Au: The Sonar of Dolphins (Springer-Verlag, Berlin, Heidelberg 1993)

    Google Scholar 

  68. B. Barshan, R. Kuc: Bat-like sonar system strategies for mobile robots, Proc. IEEE Int. Conf. Syst. Man Cybern. (1991)

    Google Scholar 

  69. R. Kuc: Biologically motivated adaptive sonar, J. Acoust. Soc. Am. 100(3), 1849–1854 (1996)

    Article  Google Scholar 

  70. V.A. Walker, H. Peremans, J.C.T. Hallam: One tone, two ears, three dimensions: A robotic investigation of pinnae movements used by rhinolophid and hipposiderid bats, J. Acoust. Soc. Am. 104, 569–579 (1998)

    Article  Google Scholar 

  71. R. Kuc: Biomimetic sonar system recognizes objects using binaural information, J. Acoust. Soc. Am. 102(2), 689–696 (1997)

    Article  Google Scholar 

  72. R. Kuc: Recognizing retro-reflectors with an obliquely-oriented multi-point sonar and acoustic flow, Int. J. Robot. Res. 22(2), 129–145 (2003)

    Article  Google Scholar 

  73. R. Mueller, R. Kuc: Foliage echoes: A probe into the ecological acoustics of bat echolocation, J. Acoust. Soc. Am. 108(2), 836–845 (2000)

    Article  Google Scholar 

  74. T. Horiuchi, T. Swindell, D. Sander, P. Abshire: A low-power CMOS neural amplifier with amplitude measurements for spike sorting, ISCAS, Vol. IV (2004) pp. 29–32

    Google Scholar 

  75. R. Kuc: Neuromorphic processing of moving sonar data for estimating passing range, IEEE Sens. J. – Special Issue on Intelligent Sensors 7(5), 851–859 (2007)

    Google Scholar 

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Authors and Affiliations

  1. Department of Electrical and Computer Systems Engineering, Monash University, Department of ECSEng, 3800, Monash, VIC, Australia

    Lindsay Kleeman Prof

  2. Department of Electrical Engineering, Yale University, 10 Hillhouse Ave, 06520-8267, New Haven, CT, USA

    Roman Kuc Dr.

Authors
  1. Lindsay Kleeman Prof
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  2. Roman Kuc Dr.
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Correspondence to Lindsay Kleeman Prof or Roman Kuc Dr. .

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Editors and Affiliations

  1. PRISMA Lab, Dipartimento di Informatica e Sistemistica, Universitá degli Studi di Napoli Federico II, 80125, Napoli, Italy, Via Claudio 21

    Bruno Siciliano Prof.

  2. Artificial Intelligence Laboratory, Department of Computer Science, Stanford University, 94305-9010, Stanford, CA, USA

    Oussama Khatib Prof.

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Kleeman, L., Kuc, R. (2008). Sonar Sensing. In: Siciliano, B., Khatib, O. (eds) Springer Handbook of Robotics. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30301-5_22

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  • DOI: https://doi.org/10.1007/978-3-540-30301-5_22

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-23957-4

  • Online ISBN: 978-3-540-30301-5

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