Search Results for author: Jesse Hagenaars

Found 4 papers, 0 papers with code

Direct learning of home vector direction for insect-inspired robot navigation

no code implementations6 May 2024 Michiel Firlefyn, Jesse Hagenaars, Guido de Croon

Drawing inspiration from the learning flights of honey bees and wasps, we propose a robot navigation method that directly learns the home vector direction from visual percepts during a learning flight in the vicinity of the nest.

Navigate Robot Navigation

Self-Supervised Learning of Event-Based Optical Flow with Spiking Neural Networks

no code implementations NeurIPS 2021 Jesse Hagenaars, Federico Paredes-Vallés, Guido de Croon

We focus on the complex task of learning to estimate optical flow from event-based camera inputs in a self-supervised manner, and modify the state-of-the-art ANN training pipeline to encode minimal temporal information in its inputs.

Event-based Optical Flow Optical Flow Estimation +1

Neuromorphic control for optic-flow-based landings of MAVs using the Loihi processor

no code implementations1 Nov 2020 Julien Dupeyroux, Jesse Hagenaars, Federico Paredes-Vallés, Guido de Croon

However, a major challenge for using such processors on robotic platforms is the reality gap between simulation and the real world.

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