Papers
5
Total Citations
31
H-Index
3
About
Gabriel Bustamante is a researcher in robotics and auditory perception, specializing in active binaural localization. His work focuses on overcoming fundamental limitations of static sound localization—such as front-back confusion and distance non-observability—by integrating motor commands with audio signals. Bustamante’s key contribution is the development of information-based feedback control frameworks that enable robotic systems to actively move their sensors to improve source localization accuracy. His most-cited paper, "An information based feedback control for audio-motor binaural localization" (2017, 11 citations), introduces a scheme that uses stochastic filtering to guide sensor motion, while his earlier work, "A three-stage framework to active source localization from a binaural head" (2015, 10 citations), provides a foundational architecture for active listening. He also advanced multi-step-ahead control strategies (2017, 6 citations) to refine real-time localization. Bustamante’s research was conducted within the EU-funded TWO!EARS project (FP7-ICT-2013-C), which explored active listening and cross-modal integration. His work is highly relevant for robotics, human-robot interaction, and auditory scene understanding, offering practical solutions for machines to navigate and interact with complex acoustic environments.
Research Focus
Key Achievements
Top Papers
- 1An information based feedback control for audio-motor binaural localization11 citations · 2017
- 2A three-stage framework to active source localization from a binaural head10 citations · 2015
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