62 citations · 64 across the 3 of their papers we have counts for
4 papers
Direct learning of home vector direction for insect-inspired robot navigation
Michiel Firlefyn, Jesse Hagenaars, Guido de Croon
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 rema…
Evolving-to-Learn Reinforcement Learning Tasks with Spiking Neural Networks
J. Lu, J. J. Hagenaars, G. C. H. E. de Croon
Inspired by the natural nervous system, synaptic plasticity rules are applied to train spiking neural networks with local information, making them suitable for online learning on n…
Self-Supervised Learning of Event-Based Optical Flow with Spiking Neural Networks
Jesse Hagenaars, Federico Paredes-Vallés, Guido de Croon
The field of neuromorphic computing promises extremely low-power and low-latency sensing and processing. Challenges in transferring learning algorithms from traditional artificial…
Evolved Neuromorphic Control for High Speed Divergence-based Landings of MAVs
J. J. Hagenaars, F. Paredes-Vallés, S. M. Bohté +1
Flying insects are capable of vision-based navigation in cluttered environments, reliably avoiding obstacles through fast and agile maneuvers, while being very efficient in the pro…