ArticleFrontiers in neuroscience2020
An On-chip Spiking Neural Network for Estimation of the Head Pose of the iCub Robot.
Article in Frontiers in neuroscience, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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5 citing papers in PubMed.
- Spiking Neural Networks in Imaging: A Review and Case Study.Sensors (Basel, Switzerland) · 2025Review
- Ring Attractors as the Basis of a Biomimetic Navigation System.Biomimetics (Basel, Switzerland) · 2023Article
- Exploiting semantic information in a spiking neural SLAM system.Frontiers in neuroscience · 2023Article
- Embodied neuromorphic intelligence.Nature communications · 2022Review
- Benchmarking Neuromorphic Hardware and Its Energy Expenditure.Frontiers in neuroscience · 2022Article
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Authors and funding
7 authors.
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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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