# Localization of Simultaneous Moving Sound Sources for Mobile Robot Using a Frequency-Domain Steered Beamformer Approach

arXiv: https://arxiv.org/abs/1602.08629 · HTML: https://mlsanity.com/paper/1602.08629/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 27 Feb 2016.

## Built on by (most cited first, 4 of 4)

- [Catch Me If You Hear Me: Audio-Visual Navigation in Complex Unmapped Environments with Moving Sounds](https://mlsanity.com/paper/2111.14843/) (2021)
- [PhaseCoder: Microphone Geometry-Agnostic Spatial Audio Understanding for Multimodal LLMs](https://mlsanity.com/paper/2601.21124/) (2026)
- [What Makes Sound Event Localization and Detection Difficult? Insights from Error Analysis](https://mlsanity.com/paper/2107.10469/) (2021)
- [NeuralMUSIC: A Hybrid Neural-Subspace Framework for Robot Sound Source Localization](https://mlsanity.com/paper/2606.18664/) (2026)

## Abstract (arXiv)

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.