activity
20172022
most citedSelf-Supervised Learning of Event-Based Optical Flow with Spiking Neural Networks

62 citations · 76 across the 10 of their papers we have counts for

collaborators

18 papers

cs.LG20224 cited

Tiny Robot Learning: Challenges and Directions for Machine Learning in Resource-Constrained Robots

Sabrina M. Neuman, Brian Plancher, Bardienus P. Duisterhof +8

Machine learning (ML) has become a pervasive tool across computing systems. An emerging application that stress-tests the challenges of ML system design is tiny robot learning, the…

cs.NE20222 cited

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…

cs.RO20224 cited

An Experimental Study of Wind Resistance and Power Consumption in MAVs with a Low-Speed Multi-Fan Wind System

Diana A. Olejnik, Sunyi Wang, Julien Dupeyroux +4

This paper discusses a low-cost, open-source and open-hardware design and performance evaluation of a low-speed, multi-fan wind system dedicated to micro air vehicle (MAV) testing.…

cs.RO2021

Design and implementation of a parsimonious neuromorphic PID for onboard altitude control for MAVs using neuromorphic processors

Stein Stroobants, Julien Dupeyroux, Guido de Croon

The great promises of neuromorphic sensing and processing for robotics have led researchers and engineers to investigate novel models for robust and reliable control of autonomous…

cs.RO20212 cited

Sniffy Bug: A Fully Autonomous Swarm of Gas-Seeking Nano Quadcopters in Cluttered Environments

Bardienus P. Duisterhof, Shushuai Li, Javier Burgués +2

Nano quadcopters are ideal for gas source localization (GSL) as they are safe, agile and inexpensive. However, their extremely restricted sensors and computational resources make G…

cs.CV20211 cited

Self-Supervised Monocular Depth Estimation of Untextured Indoor Rotated Scenes

Benjamin Keltjens, Tom van Dijk, Guido de Croon

Self-supervised deep learning methods have leveraged stereo images for training monocular depth estimation. Although these methods show strong results on outdoor datasets such as K…