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An On-chip Spiking Neural Network for Estimation of the Head Pose of the iCub Robot


Kreiser, Raphaela; Renner, Alpha; Leite, Vanessa R C; Serhan, Baris; Bartolozzi, Chiara; Glover, Arren; Sandamirskaya, Yulia (2020). An On-chip Spiking Neural Network for Estimation of the Head Pose of the iCub Robot. Frontiers in Neuroscience, 14:551.

Abstract

In this work, we present a neuromorphic architecture for head pose estimation and scene representation for the humanoid iCub robot. The spiking neuronal network is fully realized in Intel's neuromorphic research chip, Loihi, and precisely integrates the issued motor commands to estimate the iCub's head pose in a neuronal path-integration process. The neuromorphic vision system of the iCub is used to correct for drift in the pose estimation. Positions of objects in front of the robot are memorized using on-chip synaptic plasticity. We present real-time robotic experiments using 2 degrees of freedom (DoF) of the robot's head and show precise path integration, visual reset, and object position learning on-chip. We discuss the requirements for integrating the robotic system and neuromorphic hardware with current technologies.

Abstract

In this work, we present a neuromorphic architecture for head pose estimation and scene representation for the humanoid iCub robot. The spiking neuronal network is fully realized in Intel's neuromorphic research chip, Loihi, and precisely integrates the issued motor commands to estimate the iCub's head pose in a neuronal path-integration process. The neuromorphic vision system of the iCub is used to correct for drift in the pose estimation. Positions of objects in front of the robot are memorized using on-chip synaptic plasticity. We present real-time robotic experiments using 2 degrees of freedom (DoF) of the robot's head and show precise path integration, visual reset, and object position learning on-chip. We discuss the requirements for integrating the robotic system and neuromorphic hardware with current technologies.

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Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:07 Faculty of Science > Institute of Neuroinformatics
Dewey Decimal Classification:570 Life sciences; biology
Scopus Subject Areas:Life Sciences > General Neuroscience
Language:English
Date:23 June 2020
Deposited On:16 Feb 2021 09:23
Last Modified:01 Mar 2021 16:31
Publisher:Frontiers Research Foundation
ISSN:1662-453X
OA Status:Gold
Free access at:PubMed ID. An embargo period may apply.
Publisher DOI:https://doi.org/10.3389/fnins.2020.00551
PubMed ID:32655350

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