Localization of Simultaneous Moving Sound Sources for Mobile Robot Using a Frequency-Domain Steered Beamformer Approach
This enables mobile robots to complement vision for tasks like person localization, but it is incremental as it builds on existing steered beamformer approaches.
The paper tackled the problem of localizing multiple moving sound sources in 3D space for mobile robots, achieving real-time localization over 5 meters with a 200 ms response time using an 8-microphone array.
Mobile robots in real-life settings would benefit from being able to localize sound sources. Such a capability can nicely complement vision to help localize a person or an interesting event in the environment, and also to provide enhanced processing for other capabilities such as speech recognition. In this paper we present a robust sound source localization method in three-dimensional space using an array of 8 microphones. The method is based on a frequency-domain implementation of a steered beamformer along with a probabilistic post-processor. Results show that a mobile robot can localize in real time multiple moving sources of different types over a range of 5 meters with a response time of 200 ms.