[HTML][HTML] Swarms of unmanned aerial vehicles—a survey

A Tahir, J Böling, MH Haghbayan, HT Toivonen… - Journal of Industrial …, 2019 - Elsevier
The unmanned aerial vehicles or drones come in a great diversity depending upon the basic
frameworks with their particular specifications. The purpose of this study is to analyse the …

Autonomous flight

S Tang, V Kumar - Annual Review of Control, Robotics, and …, 2018 - annualreviews.org
This review surveys the current state of the art in the development of unmanned aerial
vehicles, focusing on algorithms for quadrotors. Tremendous progress has been made …

Accurate tracking of aggressive quadrotor trajectories using incremental nonlinear dynamic inversion and differential flatness

E Tal, S Karaman - IEEE Transactions on Control Systems …, 2020 - ieeexplore.ieee.org
Autonomous unmanned aerial vehicles (UAVs) that can execute aggressive (ie, high-speed
and high-acceleration) maneuvers have attracted significant attention in the past few years …

Robust constrained learning-based NMPC enabling reliable mobile robot path tracking

CJ Ostafew, AP Schoellig… - The International Journal …, 2016 - journals.sagepub.com
This paper presents a Robust Constrained Learning-based Nonlinear Model Predictive
Control (RC-LB-NMPC) algorithm for path-tracking in off-road terrain. For mobile robots …

Low-level control of a quadrotor with deep model-based reinforcement learning

NO Lambert, DS Drew, J Yaconelli… - IEEE Robotics and …, 2019 - ieeexplore.ieee.org
Designing effective low-level robot controllers often entail platform-specific implementations
that require manual heuristic parameter tuning, significant system knowledge, or long design …

Adaptive trajectory tracking control of output constrained multi‐rotors systems

Z Zuo, C Wang - IET Control Theory & Applications, 2014 - Wiley Online Library
The design of output constrained control system for unmanned aerial vehicles deployed in
confined areas is an important issue in practice and not taken into account in many autopilot …

Learning‐based nonlinear model predictive control to improve vision‐based mobile robot path tracking

CJ Ostafew, AP Schoellig, TD Barfoot… - Journal of Field …, 2016 - Wiley Online Library
This paper presents a Learning‐based Nonlinear Model Predictive Control (LB‐NMPC)
algorithm to achieve high‐performance path tracking in challenging off‐road terrain through …

Automated aerial suspended cargo delivery through reinforcement learning

A Faust, I Palunko, P Cruz, R Fierro, L Tapia - Artificial Intelligence, 2017 - Elsevier
Cargo-bearing unmanned aerial vehicles (UAVs) have tremendous potential to assist
humans by delivering food, medicine, and other supplies. For time-critical cargo delivery …

Modified central force optimization (MCFO) algorithm for 3D UAV path planning

Y Chen, J Yu, Y Mei, Y Wang, X Su - Neurocomputing, 2016 - Elsevier
Path planning for the three-dimensional (3D) unmanned aerial vehicles (UAV) is a very
important element of the whole UAV autonomous control system. In this paper, a modified …

Learning swing-free trajectories for UAVs with a suspended load

A Faust, I Palunko, P Cruz, R Fierro… - 2013 IEEE International …, 2013 - ieeexplore.ieee.org
Attaining autonomous flight is an important task in aerial robotics. Often flight trajectories are
not only subject to unknown system dynamics, but also to specific task constraints. This …