single-rb.php

JRM Vol.29 No.1 pp. 168-176
doi: 10.20965/jrm.2017.p0168
(2017)

Paper:

Evaluation of Microphone Array for Multirotor Helicopters

Takahiro Ishiki, Kai Washizaki, and Makoto Kumon

Kumamoto University
2-39-1 Kurokami, Chuo-ku, Kumamoto 860-8555, Japan

Received:
July 31, 2016
Accepted:
October 20, 2016
Published:
February 20, 2017
Keywords:
multirotor helicopter, sound source localization, rotor noise, microphone array
Abstract
High expectations are placed on the use of unmanned aerial vehicles (UAVs) in such tasks as rescue operations, which require a system that makes use of visual or auditory information to recognize the surrounding environment. As an example of such a system, this study examines the recognition of the environment using a helicopter mounted with a microphone array. Because the rotors of a helicopter generate high noise during operation, it is necessary to reduce the effects of this noise and those from other sources to record the audio signals coming from the ground with onboard microphones. In particular, because of helicopter body control, the rotor speed changes continuously and causes an unsteady rotor noise, which implies that it would be effective to arrange the microphones at a sufficient distance from the rotors. When a large microphone array is employed, however, the array weight may alter the helicopter’s flight characteristics and increase the noise, presenting a dilemma. This paper presents a model of rotor noise that takes into account the effect of the microphone array on the helicopter’s dynamic characteristics and proposes a method of evaluating the optimality of the array configuration, which is necessary for design. The validity of the proposed method is investigated using a multirotor helicopter mounted with a microphone array previously developed by the authors. In addition, an application example for locating sound sources on the ground using this helicopter is presented.
UAV with a microphone array whose performance is evaluated

UAV with a microphone array whose performance is evaluated

Cite this article as:
T. Ishiki, K. Washizaki, and M. Kumon, “Evaluation of Microphone Array for Multirotor Helicopters,” J. Robot. Mechatron., Vol.29 No.1, pp. 168-176, 2017.
Data files:
References
  1. [1] Y. Sasaki, S. Kagami, and H. Mizoguchi, “Multiple sound source mapping for a mobile robot by self-motion triangulation,” Proc. of 2006 IEEE/RSJ Int. Conf. on Intelligent Robots and Systems, pp. 380-385, 2006.
  2. [2] Y. Sasaki, M. Kaneyoshi, S. Kagami, H. Mizoguchi, and T. Enomoto, “Pitch-cluster-map based daily sound recognition for mobile robot audition,” J. of Robotics and Mechatronics, Vol.22, No.3, pp. 402-410, 2010.
  3. [3] J. Even, N. Kallakuri, L. Y. Morales, C. Ishi, and N. Hagita, “Creation of radiated sound intensity maps using multi-modal measurements onboard an autonomous mobile platform,” Proc. of 2013 IEEE/RSJ Int. Conf. on Intelligent Robots and Systems, pp. 3433-3438, 2013.
  4. [4] M. Kumon and S. Uozumi, “Binaural localization for a mobile sound source,” J. of Biomechanical Science and Engineering, Vol.6, No.1, pp. 26-39, 2011.
  5. [5] R. O. Schmidt, “Multiple emitter location and signal parameter estimation,” IEEE Trans. on Antennas and Propagation, Vol.34, No.3, pp. 276-280, 1986.
  6. [6] K. Nakamura, K. Nakadai, F. Asano, Y. Hasegawa, and H. Tsujino, “Intelligent sound source localization for dynamic environments,” 2009 IEEE/RSJ Int. Conf. on Intelligent Robots and Systems, October 11-15, 2009, St. Louis, MO, USA, pp. 664-669, 2009.
  7. [7] K. Okutani, T. Yoshida, K. Nakamura, and K. Nakadai, “Outdoor auditory scene analysis using a moving microphone array embedded in a quadrocopter,” Proc. of 2012 IEEE/RSJ Int. Conf. on Intelligent Robots and Systems, pp. 3288-3293, 2012.
  8. [8] T. Ohata, K. Nakamura, T. Mizumoto, T. Tezuka, and K. Nakadai, “Improvement in outdoor sound source detection using a quadrotor-embedded microphone array,” Proc. of 2014 IEEE/RSJ Int. Conf. on Intelligent Robots and Systems, pp. 1902-1907, 2014.
  9. [9] K. Furukawa, K. Okutani, K. Nagira, T. Otsuka, K. Itoyama, K. Nakadai, and H. G. Okuno, “Noise correlation matrix estimation for improving sound source localization by multirotor UAV,” Proc. of 2013 IEEE/RSJ Int. Conf. on Intelligent Robots and Systems, pp. 3943-3948, 2013.
  10. [10] M. Basiri, F. S. Schill, P. U. Lima, and D. Floreano, “Robust acoustic source localization of emergency signals from micro air vehicles,” Proc. of 2012 IEEE/RSJ Int. Conf. on Intelligent Robots and Systems, pp. 4737-4742, 2012.
  11. [11] M. Basiri, F. Schill, D. Floreano, and P. Lima, “Audio-based relative positioning system for multiple micro air vehicle systems,” Proc. of Robotics: Science and Systems 2013 (RSS2013), 2013.
  12. [12] M. Kumon and T. Ishiki, “A microphone array configuration for an auditory quadrotor helicopter system,” Proc. of the 12 th IEEE Int. Symposium on Safety, Security and Rescue Robotics, p. 34, 2014.
  13. [13] T. Ishiki and M. Kumon, “Design model of microphone arrays for multirotor helicopters,” 2015 IEEE/RSJ Int. Conf. on Intelligent Robots and Systems (IROS 2015), Hamburg, Germany, Sep. 28 to Oct. 2, 2015, pp. 6143-6148, 2015.
  14. [14] M. Munekata, Y. Chono, Y. Yokoyama, D. Tsuji, and H. Yoshikawa, “Characteristics of flow field around quad-rotor in hovering,” Proc. of The 5th Asian Joint Workshop on Thermophysics and Fluid Science 2014, 2014.
  15. [15] A. Tayebi and S. McGilvray, “Attitude stabilization of a VTOL quadrotor aircraft,” IEEE Trans. Contr. Sys. Techn., Vol.14, No.3, pp. 562-571, 2006.
  16. [16] M. J. Lighthill, “On sound generated aerodynamically. I. General theory,” Proc. of the Royal Society A, Vol.211, No.1107, pp. 564-587, 1952.

*This site is desgined based on HTML5 and CSS3 for modern browsers, e.g. Chrome, Firefox, Safari, Edge, Opera.

Last updated on Oct. 11, 2024