Application of event cameras and neuromorphic computing to VSLAM: A survey
Simultaneous Localization and Map** (SLAM) is a crucial function for most autonomous
systems, allowing them to both navigate through and create maps of unfamiliar …
systems, allowing them to both navigate through and create maps of unfamiliar …
Crossing the cleft: communication challenges between neuroscience and artificial intelligence
Historically, neuroscience principles have heavily influenced artificial intelligence (AI), for
example the influence of the perceptron model, essentially a simple model of a biological …
example the influence of the perceptron model, essentially a simple model of a biological …
NeuroSLAM: A brain-inspired SLAM system for 3D environments
Roboticists have long drawn inspiration from nature to develop navigation and simultaneous
localization and map** (SLAM) systems such as RatSLAM. Animals such as birds and …
localization and map** (SLAM) systems such as RatSLAM. Animals such as birds and …
[HTML][HTML] GPUs outperform current HPC and neuromorphic solutions in terms of speed and energy when simulating a highly-connected cortical model
While neuromorphic systems may be the ultimate platform for deploying spiking neural
networks (SNNs), their distributed nature and optimization for specific types of models …
networks (SNNs), their distributed nature and optimization for specific types of models …
The importance of space and time for signal processing in neuromorphic agents: the challenge of develo** low-power, autonomous agents that interact with the …
G Indiveri, Y Sandamirskaya - IEEE Signal Processing …, 2019 - ieeexplore.ieee.org
Artificial neural networks (ANNs) and computational neuroscience models have made
tremendous progress, enabling us to achieve impressive results in artificial intelligence …
tremendous progress, enabling us to achieve impressive results in artificial intelligence …
Emergent visual sensors for autonomous vehicles
For vehicles to navigate autonomously, they need to perceive and understand their
immediate surroundings. Currently, cameras are the preferred sensors, due to their high …
immediate surroundings. Currently, cameras are the preferred sensors, due to their high …
Spiking neural networks for visual place recognition via weighted neuronal assignments
Spiking neural networks (SNNs) offer both compelling potential advantages, including
energy efficiency and low latencies and challenges including the non-differentiable nature of …
energy efficiency and low latencies and challenges including the non-differentiable nature of …
[HTML][HTML] Deploying and optimizing embodied simulations of large-scale spiking neural networks on HPC infrastructure
Simulating the brain-body-environment trinity in closed loop is an attractive proposal to
investigate how perception, motor activity and interactions with the environment shape brain …
investigate how perception, motor activity and interactions with the environment shape brain …
An on-chip spiking neural network for estimation of the head pose of the iCub robot
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 …
representation for the humanoid iCub robot. The spiking neuronal network is fully realized in …
Toward cognitive navigation: Design and implementation of a biologically inspired head direction cell network
As a vital cognitive function of animals, the navigation skill is first built on the accurate
perception of the directional heading in the environment. Head direction cells (HDCs), found …
perception of the directional heading in the environment. Head direction cells (HDCs), found …