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Embedded neuromorphic vision for humanoid robots


Bartolozzi, C; Rea, F; Clercq, C; Hofstätter, M; Fasnacht, D B; Indiveri, G; Metta, G (2011). Embedded neuromorphic vision for humanoid robots. In: CVPR 2011 WORKSHOPS / IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), Colorado Springs, CO, USA, 20 June 2011 - 25 June 2011. Institute of Electrical and Electronics Engineers, 129-135.

Abstract

We are developing an embedded vision system for the humanoid robot iCub, inspired by the biology of the mammalian visual system, including concepts such as stimulus-driven, asynchronous signal sensing and processing. It comprises stimulus-driven sensors, a dedicated embedded processor and an event-based software infrastructure for processing visual stimuli. These components are integrated with the existing standard machine vision modules currently implemented on the robot, in a configuration that exploits the best features of both: the high resolution, color, frame-based vision and the neuromorphic low redundancy, wide dynamic range and high temporal resolution event-based sensors. This approach seeks to combine various styles of vision hardware with sensorimotor systems to complement and extend the current state-of-the art.

Abstract

We are developing an embedded vision system for the humanoid robot iCub, inspired by the biology of the mammalian visual system, including concepts such as stimulus-driven, asynchronous signal sensing and processing. It comprises stimulus-driven sensors, a dedicated embedded processor and an event-based software infrastructure for processing visual stimuli. These components are integrated with the existing standard machine vision modules currently implemented on the robot, in a configuration that exploits the best features of both: the high resolution, color, frame-based vision and the neuromorphic low redundancy, wide dynamic range and high temporal resolution event-based sensors. This approach seeks to combine various styles of vision hardware with sensorimotor systems to complement and extend the current state-of-the art.

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Additional indexing

Item Type:Conference or Workshop Item (Speech), refereed, original work
Communities & Collections:07 Faculty of Science > Institute of Neuroinformatics
Dewey Decimal Classification:570 Life sciences; biology
Scopus Subject Areas:Physical Sciences > Computer Vision and Pattern Recognition
Physical Sciences > Electrical and Electronic Engineering
Language:English
Event End Date:25 June 2011
Deposited On:03 Sep 2014 12:39
Last Modified:30 May 2022 08:50
Publisher:Institute of Electrical and Electronics Engineers
Series Name:2011 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)
Number of Pages:1
ISSN:2160-7508
OA Status:Green
Publisher DOI:https://doi.org/10.1109/CVPRW.2011.5981834
Official URL:https://ieeexplore.ieee.org/document/5981834
Other Identification Number:IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)

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