Learning quadrotor dynamics for precise, safe, and agile flight control

A Saviolo, G Loianno - Annual Reviews in Control, 2023 - Elsevier
This article reviews the state-of-the-art modeling and control techniques for aerial robots
such as quadrotor systems and presents several future research directions in this area. The …

Review of aerial transportation of suspended-cable payloads with quadrotors

J Estevez, G Garate, JM Lopez-Guede, M Larrea - Drones, 2024 - mdpi.com
Payload transportation and manipulation by rotorcraft drones are receiving a lot of attention
from the military, industrial and logistics research areas. The interactions between the UAV …

Neural-fly enables rapid learning for agile flight in strong winds

M O'Connell, G Shi, X Shi, K Azizzadenesheli… - Science Robotics, 2022 - science.org
Executing safe and precise flight maneuvers in dynamic high-speed winds is important for
the ongoing commoditization of uninhabited aerial vehicles (UAVs). However, because the …

Autonomous drone racing: A survey

D Hanover, A Loquercio, L Bauersfeld… - IEEE Transactions …, 2024 - ieeexplore.ieee.org
Over the last decade, the use of autonomous drone systems for surveying, search and
rescue, or last-mile delivery has increased exponentially. With the rise of these applications …

A control architecture to coordinate energy management with trajectory tracking control for fuel cell/battery hybrid unmanned aerial vehicles

H Liu, Y Yao, J Wang, Y Qin, T Li - International Journal of Hydrogen …, 2022 - Elsevier
Fuel cell/battery hybrid energy storage system (HESS) powered unmanned aerial vehicle
(UAV) has the outstanding advantage of long endurance time. Trajectory tracking motion is a …

Symmetric actor–critic deep reinforcement learning for cascade quadrotor flight control

H Han, J Cheng, Z Xi, M Lv - Neurocomputing, 2023 - Elsevier
Even though deep reinforcement learning (DRL) has been extensively applied to quadrotor
flight control to simplify parameter adjustment, it has some drawbacks in terms of control …

Difftune: Auto-tuning through auto-differentiation

S Cheng, M Kim, L Song, C Yang, Y Jin… - IEEE Transactions …, 2024 - ieeexplore.ieee.org
The performance of robots in high-level tasks depends on the quality of their lower level
controller, which requires fine-tuning. However, the intrinsically nonlinear dynamics and …

Bayesian multi-task learning mpc for robotic mobile manipulation

E Arcari, MV Minniti, A Scampicchio… - IEEE Robotics and …, 2023 - ieeexplore.ieee.org
Mobile manipulation in robotics is challenging due to the need to solve many diverse tasks,
such as opening a door or picking-and-placing an object. Typically, a basic first-principles …

Perception-aware perching on powerlines with multirotors

JL Paneque, JR Martínez-de Dios… - IEEE Robotics and …, 2022 - ieeexplore.ieee.org
Multirotor aerial robots are becoming widely used for the inspection of powerlines. To
enable continuous, robust inspection without human intervention, the robots must be able to …

Online dynamics learning for predictive control with an application to aerial robots

TZ Jiahao, KY Chee, MA Hsieh - Conference on Robot …, 2023 - proceedings.mlr.press
In this work, we consider the task of improving the accuracy of dynamic models for model
predictive control (MPC) in an online setting. Although prediction models can be learned …