Optical Flow Determination using Neuromorphic Hardware with Integrate & Fire Neurons

Spiking neural networks implemented for sensing and control of robots have the potential to achieve lower latency and power consumption by processing information sparsely and asynchronously. They have been used on neuromorphic devices to estimate optical flow for micro air vehicles navigation, however robotic implementations have been limited to...

Direct Learning of Home Vector Direction: Incited by Existing Insect-Inspired Approaches for Local Navigation and Wayfinding

Insects have long been recognized for their ability to navigate and return home using visual cues from their nest’s environment. However, the precise mechanism underlying this remarkable homing skill remains a subject of ongoing investigation. Drawing inspiration from the learning flights of honey bees and wasps, we propose a robot navigation...

Memory Mechanisms in Spiking Neural Networks

Neuromorphic sensors, like for example event cameras, detect incremental changes in the sensed quantity and communicate these via a stream of events. Desired properties of these signals such as high temporal resolution and asynchrony are not always fully exploited by algorithms that process these signals. Spiking neural networks (SNNs) have...