Zobrazeno 1 - 10
of 162
pro vyhledávání: '"de Croon, Guido C. H. E."'
The real-world application of small drones is mostly hampered by energy limitations. Neuromorphic computing promises extremely energy-efficient AI for autonomous flight, but is still challenging to train and deploy on real robots. In order to reap th
Externí odkaz:
http://arxiv.org/abs/2411.13945
Relative localization (RL) is essential for the successful operation of micro air vehicle (MAV) swarms. Achieving accurate 3-D RL in infrastructure-free and GPS-denied environments with only distance information is a challenging problem that has not
Externí odkaz:
http://arxiv.org/abs/2405.18234
Motion detection is a primary task required for robotic systems to perceive and navigate in their environment. Proposed in the literature bioinspired neuromorphic Time-Difference Encoder (TDE-2) combines event-based sensors and processors with spikin
Externí odkaz:
http://arxiv.org/abs/2402.11662
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 obstacle avoidance pipeline based on reinforcement learning. This pip
Externí odkaz:
http://arxiv.org/abs/2402.08381
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-affine dynamics. Traditional solutions employ multi-state switched logic co
Externí odkaz:
http://arxiv.org/abs/2311.09185
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 fully autonomous orographic soaring without a priori knowledge of the w
Externí odkaz:
http://arxiv.org/abs/2308.00565
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 addresses position control challenges by introducing a target gradien
Externí odkaz:
http://arxiv.org/abs/2305.13891
Autor:
Izzo, Dario, Blazquez, Emmanuel, Ferede, Robin, Origer, Sebastien, De Wagter, Christophe, de Croon, Guido C. H. E.
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 mission. Sensorimotor actions are thus often derived from high-level, q
Externí odkaz:
http://arxiv.org/abs/2305.13078
Autor:
Origer, Sebastien, De Wagter, Christophe, Ferede, Robin, de Croon, Guido C. H. E., Izzo, Dario
Reaching fast and autonomous flight requires computationally efficient and robust algorithms. To this end, we train Guidance & Control Networks to approximate optimal control policies ranging from energy-optimal to time-optimal flight. We show that t
Externí odkaz:
http://arxiv.org/abs/2305.02705
Developing optimal controllers for aggressive high-speed quadcopter flight poses significant challenges in robotics. Recent trends in the field involve utilizing neural network controllers trained through supervised or reinforcement learning. However
Externí odkaz:
http://arxiv.org/abs/2304.13460