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

Frontiers in Neuroscience

Raphaela Kreiser¹  Yulia Sandamirskaya¹  Vanessa R. C. Leite¹  Alpha Renner¹  Arren Glover²  Chiara Bartolozzi²  Baris Serhan³ 

[1] Institute of Neuroinformatics, University of Zurich and ETH Zurich, Zurich, Switzerland;Istituto Italiano di Tecnologia, Genoa, Italy;Lincoln Centre for Autonomous Systems, University of Lincoln, Lincoln, United Kingdom;

关键词: pose estimation;    event-based vision;    neuromorphic SLAM;    on-chip learning;    scene memory;    iCub robot;   

DOI  :  10.3389/fnins.2020.00551

来源: DOAJ

【 摘 要 】

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.

【 授权许可】

Unknown