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A neuromorphic approach of the sound source localization task in real-time embedded systems: work-in-progress

Authors:

Daniel Gutierrez-Galan,

Juan Pedro Dominguez-Morales,

Angel Jimenez-Fernandez,

Ricardo Tapiador-Morales,

Antonio Rios-Navarro,

Alejandro Linares-BarrancoAuthors Info & Claims

EMSOFT '19: Proceedings of the International Conference on Embedded Software Companion

Article No.: 10, Pages 1 - 2

https://doi.org/10.1145/3349568.3351544

Published: 13 October 2019 Publication History

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Abstract

Autonomous robots have become a very popular topic within the artificial intelligence field. These systems are able to perform difficult or risky tasks that could be dangerous when done by humans or trained animals. Vision is commonly considered the most relevant input sensor for autonomous robots and tracking systems. However, auditory information is also important in some specific situations where vision cannot provide any useful information when navigating. In this work, a spike-based model of the medial superior olive of the inner ear has been implemented in reconfigurable hardware for performing sound source localization in real time. Future works will focus on integrating this information with vision in order to achieve a fully bio-inspired autonomous tracking system.

References

[1]

Lloyd A Jeffress. 1948. A place theory of sound localization. Journal of comparative and physiological psychology 41,1 (1948), 35.

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[2]

Angel Jimenez-Fernandez et al. 2010. Building blocks for spikes signals processing. In Neural Networks (IJCNN), The 2010 International Joint Conference on. IEEE, 1--8.

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[3]

Angel Jiménez-Fernández et al. 2017. A Binaural Neuromorphic Auditory Sensor for FPGA: A Spike Signal Processing Approach. IEEE Trans. Neural Netw. Learning Syst. 28, 4 (2017), 804--818.

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[4]

Qian Liu et al. 2013. Modeling populations of spiking neurons for fine timing sound localization. In The 2013 International Joint Conference on Neural Networks (IJCNN). IEEE, 1--8.

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Cited By

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Gutierrez-Galan DBartolozzi CDominguez-Morales JJimenez-Fernandez ALinares-Barranco A(2022)Towards the Neuromorphic Implementation of the Auditory Perception in the iCub Robotic PlatformProceedings of the 2022 Annual Neuro-Inspired Computational Elements Conference10.1145/3517343.3517347(11-12)Online publication date: 28-Mar-2022
https://dl.acm.org/doi/10.1145/3517343.3517347

Index Terms

A neuromorphic approach of the sound source localization task in real-time embedded systems: work-in-progress
1. Applied computing
  1. Enterprise computing
    1. Event-driven architectures

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Published In

EMSOFT '19: Proceedings of the International Conference on Embedded Software Companion

October 2019

31 pages

ISBN:9781450369244

DOI:10.1145/3349568

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 13 October 2019

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ESWEEK '19

ESWEEK '19: Fifteenth Embedded Systems Week

October 13 - 18, 2019

New York, New York

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Overall Acceptance Rate 60 of 203 submissions, 30%

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Gutierrez-Galan DBartolozzi CDominguez-Morales JJimenez-Fernandez ALinares-Barranco A(2022)Towards the Neuromorphic Implementation of the Auditory Perception in the iCub Robotic PlatformProceedings of the 2022 Annual Neuro-Inspired Computational Elements Conference10.1145/3517343.3517347(11-12)Online publication date: 28-Mar-2022
https://dl.acm.org/doi/10.1145/3517343.3517347

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Real-time neuro-inspired sound source localization and tracking architecture applied to a robotic platform

A biologically inspired spiking neural network model of the auditory midbrain for sound source localisation

Improved sound source localization and front-back disambiguation for humanoid robots with two ears