Graph-SLAM based calibration of an embedded asynchronous microphone array for outdoor robotic target tracking

World Scientific
Publication Type:
Conference Proceeding
Assistive Robotics: Proceedings of the International Conference on CLAWAR 2015, 2015, pp. 641 - 648
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This paper presents a strategy for sound source localisation using an embedded asynchronous microphone array for robotic target tracking application. Conventional microphone array technologies require a multi-channel A/D converter for inter-microphone synchronization making the technology relatively expensive. In our method, a synchronization free embedded asynchronous microphone array has released this requirement. The microphone array needs self calibration using graph-based SLAM method, which estimates starting time offset and clock difference/drift of each microphone channel using Gauss-Newton least square optimization. Once calibrated, the asynchronous microphone array can be used to find the sound source direction using various Direction Of Arrival (DOA) estimation algorithms just like a synchronized one. The proposed method is suitable for target tracking applications. Specifically, this method is used for tracking a person with an outdoor service robot: Garden Utility Transportation System. Comprehensive simulations and experimental results are presented to show the validity of the algorithm.
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