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

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.

journal_name

Front Neurosci

authors

Kreiser R,Renner A,Leite VRC,Serhan B,Bartolozzi C,Glover A,Sandamirskaya Y

doi

10.3389/fnins.2020.00551

subject

Has Abstract

pub_date

2020-06-23 00:00:00

pages

551

eissn

1662-4548

issn

1662-453X

journal_volume

14

pub_type

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