activity
20162024
most citedEvolution of Robust High Speed Optical-Flow-Based Landing for Autonomous MAVs

17 citations · 38 across the 14 of their papers we have counts for

collaborators

14 papers

cs.NE2024

Event-based Optical Flow on Neuromorphic Processor: ANN vs. SNN Comparison based on Activation Sparsification

Yingfu Xu, Guangzhi Tang, Amirreza Yousefzadeh +2

Spiking neural networks (SNNs) for event-based optical flow are claimed to be computationally more efficient than their artificial neural networks (ANNs) counterparts, but a fair c…

cs.RO2024

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…

cs.RO20232 cited

Evolving Spiking Neural Networks to Mimic PID Control for Autonomous Blimps

Tim Burgers, Stein Stroobants, Guido de Croon

In recent years, Artificial Neural Networks (ANN) have become a standard in robotic control. However, a significant drawback of large-scale ANNs is their increased power consumptio…

cs.RO2023

AOSoar: Autonomous Orographic Soaring of a Micro Air Vehicle

Sunyou Hwang, Bart D. W. Remes, Guido C. H. E. de Croon

Utilizing wind hovering techniques of soaring birds can save energy expenditure and improve the flight endurance of micro air vehicles (MAVs). Here, we present a novel method for f…

cs.RO2023

Autonomous Control for Orographic Soaring of Fixed-Wing UAVs

Tom Suys, Sunyou Hwang, Guido C. H. E. de Croon +1

We present a novel controller for fixed-wing UAVs that enables autonomous soaring in an orographic wind field, extending flight endurance. Our method identifies soaring regions and…

cs.RO20232 cited

Guidance & Control Networks for Time-Optimal Quadcopter Flight

Sebastien Origer, Christophe De Wagter, Robin Ferede +2

Reaching fast and autonomous flight requires computationally efficient and robust algorithms. To this end, we train Guidance & Control Networks to approximate optimal control polic…