180 citations · 466 across the 15 of their papers we have counts for
15 papers
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…
End-to-end Reinforcement Learning for Time-Optimal Quadcopter Flight
Robin Ferede, Christophe De Wagter, Dario Izzo +1
Aggressive time-optimal control of quadcopters poses a significant challenge in the field of robotics. The state-of-the-art approach leverages reinforcement learning (RL) to train…
Optimality Principles in Spacecraft Neural Guidance and Control
Dario Izzo, Emmanuel Blazquez, Robin Ferede +3
Spacecraft and drones aimed at exploring our solar system are designed to operate in conditions where the smart use of onboard resources is vital to the success or failure of the m…
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…
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…
End-to-end Neural Network Based Quadcopter control
Robin Ferede, Guido C. H. E. de Croon, Christophe De Wagter +1
Developing optimal controllers for aggressive high-speed quadcopter flight poses significant challenges in robotics. Recent trends in the field involve utilizing neural network con…
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…
Onboard Ranging-based Relative Localization and Stability for Lightweight Aerial Swarms
Shushuai Li, Feng Shan, Jiangpeng Liu +3
Lightweight aerial swarms have potential applications in scenarios where larger drones fail to operate efficiently. The primary foundation for lightweight aerial swarms is efficien…
Aggressive Online Control of a Quadrotor via Deep Network Representations of Optimality Principles
Shuo Li, Ekin Ozturk, Christophe De Wagter +2
Optimal control holds great potential to improve a variety of robotic applications. The application of optimal control on-board limited platforms has been severely hindered by the…
Design, Control and Visual Navigation of the DelftaCopter
Christophe De Wagter, Rick Ruijsink, Ewoud Smeur +4
To participate in the Outback Medical Express UAV Challenge 2016, a vehicle was designed and tested that can hover precisely, take-off and land vertically, fly fast forward efficie…
First free-flight flow visualisation of a flapping-wing robot
Matěj Karásek, Mustafa Percin, Torbjørn Cunis +4
Flow visualisations are essential to better understand the unsteady aerodynamics of flapping wing flight. The issues inherent to animal experiments, such as poor controllability an…
Efficient Optical flow and Stereo Vision for Velocity Estimation and Obstacle Avoidance on an Autonomous Pocket Drone
Kimberly McGuire, Guido de Croon, Christophe De Wagter +2
Miniature Micro Aerial Vehicles (MAV) are very suitable for flying in indoor environments, but autonomous navigation is challenging due to their strict hardware limitations. This p…
Obstacle Avoidance Strategy using Onboard Stereo Vision on a Flapping Wing MAV
Sjoerd Tijmons, Guido de Croon, Bart Remes +2
The development of autonomous lightweight MAVs, capable of navigating in unknown indoor environments, is one of the major challenges in robotics. The complexity of this challenge c…
Local Histogram Matching for Efficient Optical Flow Computation Applied to Velocity Estimation on Pocket Drones
Kimberly McGuire, Guido de Croon, Christophe de Wagter +3
Autonomous flight of pocket drones is challenging due to the severe limitations on on-board energy, sensing, and processing power. However, tiny drones have great potential as thei…
Optical-Flow based Self-Supervised Learning of Obstacle Appearance applied to MAV Landing
H. W. Ho, C. De Wagter, B. D. W. Remes +1
Monocular optical flow has been widely used to detect obstacles in Micro Air Vehicles (MAVs) during visual navigation. However, this approach requires significant movement, which r…