Twin delayed deep deterministic policy gradient-based target tracking for unmanned aerial vehicle with achievement rewarding and multistage training

NA Mosali, SS Shamsudin, O Alfandi, R Omar… - IEEE …, 2022 - ieeexplore.ieee.org
Target tracking using an unmanned aerial vehicle (UAV) is a challenging robotic problem. It
requires handling a high level of nonlinearity and dynamics. Model-free control effectively …

Real-time measurement-driven reinforcement learning control approach for uncertain nonlinear systems

M Abouheaf, D Boase, W Gueaieb, D Spinello… - … Applications of Artificial …, 2023 - Elsevier
The paper introduces an interactive machine learning mechanism to process the
measurements of an uncertain, nonlinear dynamic process and hence advise an actuation …

An adaptive multi-level quantization-based reinforcement learning model for enhancing UAV landing on moving targets

N Abo Mosali, SS Shamsudin, SA Mostafa, O Alfandi… - Sustainability, 2022 - mdpi.com
The autonomous landing of an unmanned aerial vehicle (UAV) on a moving platform is an
essential functionality in various UAV-based applications. It can be added to a teleoperation …

A Survey of Offline-and Online-Learning-Based Algorithms for Multirotor Uavs

S Sönmez, MJ Rutherford, KP Valavanis - Drones, 2024 - mdpi.com
Multirotor UAVs are used for a wide spectrum of civilian and public domain applications.
Their navigation controllers include onboard sensor suites that facilitate safe, autonomous or …

An online model-following projection mechanism using reinforcement learning

MI Abouheaf, HA Hashim, MA Mayyas… - … on Automatic Control, 2023 - ieeexplore.ieee.org
In this article, we propose a model-free adaptive learning solution for a model-following
control problem. This approach employs policy iteration, to find an optimal adaptive control …

[HTML][HTML] A Vision-Based End-to-End Reinforcement Learning Framework for Drone Target Tracking

X Zhao, X Huang, J Cheng, Z Xia, Z Tu - Drones, 2024 - mdpi.com
Drone target tracking, which involves instructing drone movement to follow a moving target,
encounters several challenges:(1) traditional methods need accurate state estimation of …

Aerial interception of non-cooperative intruder using model predictive control

R Srivastava, R Lima, K Das - 2022 American Control …, 2022 - ieeexplore.ieee.org
Autonomous capture of an unknown non-cooperative aerial target is a complex task
requiring real-time target localization, trajectory prediction and control. The current work …

A data-driven model-reference adaptive control approach based on reinforcement learning

M Abouheaf, W Gueaieb, D Spinello… - … on Robotic and …, 2021 - ieeexplore.ieee.org
Model-reference adaptive systems refer to a consortium of techniques that guide plants to
track desired reference trajectories. Approaches based on theories like Lyapunov, sliding …

Integrated targeting, guidance, navigation, and control for unmanned aerial vehicles

E Kawamura - 2020 - search.proquest.com
The goal of this dissertation research is to demonstrate the integration of targeting,
guidance, navigation, and control (TGNC) functions for real-time implementation onboard …

Range estimation and visual servoing of a dynamic target using a monocular camera

R Srivastava, A Maity, R Lima… - … Conference on Unmanned …, 2020 - ieeexplore.ieee.org
This paper delves into the problem of tracking an unknown maneuvering target using only
monocular visual feedback. It is usually difficult to perform target tracking using only …