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JRM Vol.29 No.1 pp. 94-104
doi: 10.20965/jrm.2017.p0094
(2017)

Paper:

Probabilistic 3D Sound Source Mapping System Based on Monte Carlo Localization Using Microphone Array and LIDAR

Ryo Tanabe*,**, Yoko Sasaki**, and Hiroshi Takemura*,**

*Department of Mechanical Engineering, Tokyo University of Science
2641 Yamazaki, Noda-shi, Chiba 278-8510, Japan

**National Institute of Advanced Industrial Science and Technology (AIST)
2-3-26 Aomi, Kouto-ku, Tokyo 135-0064, Japan

Received:
July 23, 2016
Accepted:
November 1, 2016
Published:
February 20, 2017
Keywords:
sound source mapping, microphone array, 3D LIDAR, robot audition
Abstract

Probabilistic 3D Sound Source Mapping System Based on Monte Carlo Localization Using Microphone Array and LIDAR

3D sound source environmental map

The study proposes a probabilistic 3D sound source mapping system for a moving sensor unit. A microphone array is used for sound source localization and tracking based on the multiple signal classification (MUSIC) algorithm and a multiple-target tracking algorithm. Laser imaging detection and ranging (LIDAR) is used to generate a 3D geometric map and estimate the location of its six-degrees-of-freedom (6 DoF) using the state-of-the-art gyro-integrated iterative closest point simultaneous localization and mapping (G-ICP SLAM) method. Combining these modules provides sound detection in 3D global space for a moving robot. The sound position is then estimated using Monte Carlo localization from the time series of a tracked sound stream. The results of experiments using the hand-held sensor unit indicate that the method is effective for arbitrary motions of the sensor unit in environments with multiple sound sources.

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Last updated on Dec. 11, 2017