Title
Probabilistic 3D Sound Source Mapping System Based on Monte Carlo Localization Using Microphone Array and LIDAR.
Abstract
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.
Year
DOI
Venue
2017
10.20965/jrm.2017.p0094
JOURNAL OF ROBOTICS AND MECHATRONICS
Keywords
Field
DocType
sound source mapping,microphone array,3D LIDAR,robot audition
Computer vision,Computer science,Microphone array,Robot audition,Lidar,Artificial intelligence,Probabilistic logic,Monte Carlo localization
Journal
Volume
Issue
ISSN
29
1
0915-3942
Citations 
PageRank 
References 
1
0.34
11
Authors
3
Name
Order
Citations
PageRank
Ryo Tanabe1144.78
Yoko Sasaki28215.66
Hiroshi Takemura3119.62