180 citations · 692 across the 42 of their papers we have counts for
11 papers · 1 filter
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…
Unified incremental nonlinear controller for the transition control of a hybrid dual-axis tilting rotor quad-plane
Alessandro Mancinelli, Bart D. W. Remes, Guido C. H. E. de Croon +1
Overactuated Tilt Rotor Unmanned Aerial Vehicles are renowned for exceptional wind resistance and a broad operational range, which poses complex control challenges due to non-affin…
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…
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…
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…
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 computing for attitude estimation onboard quadrotors
Stein Stroobants, Julien Dupeyroux, Guido C. H. E. de Croon
Compelling evidence has been given for the high energy efficiency and update rates of neuromorphic processors, with performance beyond what standard Von Neumann architectures can a…
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…