Probabilistic 3D Sound Source Mapping System Based on Monte Carlo Localization Using Microphone Array and LIDAR
2017; Fuji Technology Press Ltd.; Volume: 29; Issue: 1 Linguagem: Inglês
10.20965/jrm.2017.p0094
ISSN1883-8049
AutoresRyo Tanabe, Yoko Sasaki, Hiroshi Takemura,
Tópico(s)Robotics and Sensor-Based Localization
Resumo[abstFig src='/00290001/09.jpg' width='300' text='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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