activity
20232025
most citedGuidance & Control Networks for Time-Optimal Quadcopter Flight

2 citations · 5 across the 5 of their papers we have counts for

collaborators

5 papers

cs.RO2025

Multi-objective Evolution of Drone Morphology

Elijah H. W. Ang, Christophe De Wagter, Guido C. H. E. de Croon

The design of multicopter drones has remained almost the same since its inception. While conventional designs, such as the quadcopter, work well in many cases, they may not be opti…

cs.RO20242 cited

MAVRL: Learn to Fly in Cluttered Environments with Varying Speed

Hang Yu, Christophe De Wagter, Guido C. H. E de Croon

Many existing obstacle avoidance algorithms overlook the crucial balance between safety and agility, especially in environments of varying complexity. In our study, we introduce an…

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…

cs.RO20231 cited

Neuromorphic Control using Input-Weighted Threshold Adaptation

Stein Stroobants, Christophe De Wagter, Guido C. H. E. de Croon

Neuromorphic processing promises high energy efficiency and rapid response rates, making it an ideal candidate for achieving autonomous flight of resource-constrained robots. It wi…

cs.RO2023

AvoidBench: A high-fidelity vision-based obstacle avoidance benchmarking suite for multi-rotors

Hang Yu, Guido C. H. E de Croon, Christophe De Wagter

Obstacle avoidance is an essential topic in the field of autonomous drone research. When choosing an avoidance algorithm, many different options are available, each with their adva…