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Machines
Special Issues
Advanced Control and Path Planning of Unmanned Aerial Vehicles (UAVs)
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Advanced Control and Path Planning of Unmanned Aerial Vehicles (UAVs)

A special issue of Machines (ISSN 2075-1702). This special issue belongs to the section "Robotics, Mechatronics and Intelligent Machines".

Deadline for manuscript submissions: 31 October 2025 | Viewed by 8654

Special Issue Editors

Dr. Giuseppe Silano

E-Mail Website
Guest Editor
Department of Cybernetics, Faculty of Electrical Engineering, Czech Technical University, 12135 Praha 2, Czech Republic
Interests: simulation; control and motion planning problems for unmanned aerial vehicles; formal methods in robotics and automation; model predictive control techniques; nonlinear optimization; human-robot interaction; communication-aware robotics; robot manipulators
Dr. Yahui Liu

E-Mail Website
Guest Editor
Driver-Vehicle Automation Collaboration & Shared Control Lab, School of Vehicle and Mobility, Tsinghua University, Beijing 100084, China
Interests: vehicle dynamics and control; autonomous vehicles; human-vehicle interaction; driver-vehicle automation; shared steering control
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

We are pleased to announce a Special Issue focused on the advancements and challenges in unmanned aerial vehicles (UAVs). UAVs have emerged as indispensable tools in various fields, offering remote-controlled or onboard computer-piloted aircraft capabilities. Their applications span precision agriculture, package delivery, monitoring, search and rescue operations, and more. Particularly noteworthy is their ability to safely and securely conduct inspections in high or confined spaces.

However, ensuring the safe and optimal operation of UAVs requires high-quality sensors and advanced control technology. Without these crucial components, UAVs may fail to detect potential collisions and navigate past them. Therefore, the accurate control and optimization of UAVs' paths remain key challenges in this field. As a result, research efforts have rapidly increased to enhance the accuracy and performance of UAVs.

This Special Issue aims to collect articles that cover the recent developments in UAV technology and foster the exchange of knowledge on this topic among researchers in related fields. The scope of the research for this Special Issue encompasses various aspects, including aircraft control, path planning, trajectory optimization, and target tracking, among others. We invite submissions of original research articles and reviews, as we believe they will serve as valuable resources for researchers in the future.

We look forward to receiving your contributions and collaborating together in this exciting area of UAV research.

Specific topics of interest for publication include, but are not limited to, the following:

  • Advanced control techniques for UAVs;
  • Path planning and collision avoidance algorithms for UAVs;
  • Trajectory optimization for efficient UAV operations;
  • Target tracking and object detection in UAV applications;
  • UAVs for precision agriculture and environmental monitoring;
  • UAVs in package delivery and logistics;
  • UAVs in search and rescue operations;
  • Autonomous and swarm UAV systems;
  • Sensor fusion and perception for UAVs;
  • Communication and networking solutions for UAV swarms;
  • Safety and security challenges in UAV operations;
  • Energy efficiency and battery management for UAVs;
  • Machine learning and AI for autonomous UAVs;
  • Human–drone interaction and user interfaces;
  • UAVs in remote sensing and mapping applications;
  • Regulatory and ethical considerations for UAV operations;
  • Case studies and real-world applications of UAV technology.

Dr. Giuseppe Silano
Dr. Yahui Liu
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Machines is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

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  • Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
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  • External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
  • e-Book format: Special Issues with more than 10 articles can be published as dedicated e-books, ensuring wide and rapid dissemination.

Further information on MDPI's Special Issue policies can be found here.

Published Papers (4 papers)

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Research

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31 pages, 14278 KiB  
Article
Adaptive Impedance Control of Multirotor UAV for Accurate and Robust Path Following
by Zain Ahmed and Xiaofeng Xiong
Machines 2024, 12(12), 868; https://doi.org/10.3390/machines12120868 - 29 Nov 2024
Cited by 1 | Viewed by 830
Abstract
Unmanned Aerial Vehicles (UAVs) have become essential tools in various industries for tasks such as inspection, maintenance, and surveillance. An Online Impedance Adaptive Controller (OIAC) is proposed for the online modulating of UAV control gains to obtain better performance and stability of tracking [...] Read more.
Unmanned Aerial Vehicles (UAVs) have become essential tools in various industries for tasks such as inspection, maintenance, and surveillance. An Online Impedance Adaptive Controller (OIAC) is proposed for the online modulating of UAV control gains to obtain better performance and stability of tracking curved trajectories than the traditional methods, Model Reference Adaptive Controller (MRAC) and Proportional–Integral–Derivative (PID). Two UAV path planners with minimal jerk and snap were integrated into OIAC, MRAC, and PID. These six controllers were implemented and compared in a simulated UAV with perceptional noise, which follows curved pipelines and avoids obstacles. Experimental results show that the OIAC controller achieves at least an 80% improvement over the PID controller across all trajectory types in terms of the trajectory tracking error. Additionally, OIAC demonstrates an over 20% improvement in jerk trajectories and a more than 30% improvement in snap trajectories when compared to the MRAC controller. These results indicate that OIAC offers enhanced trajectory tracking accuracy and robustness against perceptual noise. Our work presents an advanced controller of a UAV and its preliminary validation in accurate and robust path tracking. Full article
(This article belongs to the Special Issue Advanced Control and Path Planning of Unmanned Aerial Vehicles (UAVs))
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22 pages, 1006 KiB  
Article
Network-Centric Formation Control and Ad Hoc Communication with Localisation Analysis in Multi-UAV Systems
by Jack Devey, Palvir Singh Gill, George Allen, Essa Shahra and Moad Idrissi
Machines 2024, 12(8), 550; https://doi.org/10.3390/machines12080550 - 13 Aug 2024
Viewed by 2047
Abstract
In recent years, the cost-effectiveness and versatility of Unmanned Aerial Vehicles (UAVs) have led to their widespread adoption in both military and civilian applications, particularly for operations in remote or hazardous environments where human intervention is impractical. The use of multi-agent UAV systems [...] Read more.
In recent years, the cost-effectiveness and versatility of Unmanned Aerial Vehicles (UAVs) have led to their widespread adoption in both military and civilian applications, particularly for operations in remote or hazardous environments where human intervention is impractical. The use of multi-agent UAV systems has notably increased for complex tasks such as surveying and monitoring, driving extensive research and development in control, communication, and coordination technologies. Evaluating and analysing these systems under dynamic flight conditions present significant challenges. This paper introduces a mathematical model for leader–follower structured Quadrotor UAVs that encapsulates their dynamic behaviour, incorporating a novel multi-agent ad hoc coordination network simulated via COOJA. Simulation results with a pipeline surveillance case study demonstrate the efficacy of the coordination network and show that the system offers various improvements over contemporary pipeline surveillance approaches. Full article
(This article belongs to the Special Issue Advanced Control and Path Planning of Unmanned Aerial Vehicles (UAVs))
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12 pages, 961 KiB  
Communication
Geometric Attitude Fault-Tolerant Control of Quadrotor Unmanned Aerial Vehicles with Adaptive Extended State Observers
by Liping Wang, Hailong Pei and Zihuan Cheng
Machines 2024, 12(1), 47; https://doi.org/10.3390/machines12010047 - 10 Jan 2024
Cited by 2 | Viewed by 1673
Abstract
This paper is concerned with the attitude tracking problem of quadrotor unmanned aerial vehicles (UAVs) with respect to endogenous uncertainties, exogenous disturbances and actuator failures. Two different control methods are proposed to solve this problem. First, an adaptive extended state observer (AESO)-based control [...] Read more.
This paper is concerned with the attitude tracking problem of quadrotor unmanned aerial vehicles (UAVs) with respect to endogenous uncertainties, exogenous disturbances and actuator failures. Two different control methods are proposed to solve this problem. First, an adaptive extended state observer (AESO)-based control framework is devised to tackle the difficulties caused by model uncertainties and external disturbances. A fault-tolerant control method is proposed to cope with the occurrence of actuator failure, which is modeled as a constant loss of effectiveness. Another method employs AESOs to compensate for lumped disturbances, which include endogenous uncertainties, exogenous disturbances and actuator failures. Then, the error can exponentially converge to a bounded set. Finally, simulations are performed to ensure the feasibility of the designed technique. Full article
(This article belongs to the Special Issue Advanced Control and Path Planning of Unmanned Aerial Vehicles (UAVs))
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Review

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32 pages, 8047 KiB  
Review
State-of-the-Art Flocking Strategies for the Collective Motion of Multi-Robots
by Zain Anwar Ali, Eman H. Alkhammash and Raza Hasan
Machines 2024, 12(10), 739; https://doi.org/10.3390/machines12100739 - 20 Oct 2024
Cited by 1 | Viewed by 1934
Abstract
The technological revolution has transformed the area of labor with reference to automation and robotization in various domains. The employment of robots automates these disciplines, rendering beneficial impacts as robots are cost-effective, reliable, accurate, productive, flexible, and safe. Usually, single robots are deployed [...] Read more.
The technological revolution has transformed the area of labor with reference to automation and robotization in various domains. The employment of robots automates these disciplines, rendering beneficial impacts as robots are cost-effective, reliable, accurate, productive, flexible, and safe. Usually, single robots are deployed to accomplish specific tasks. The purpose of this study is to focus on the next step in robot research, collaborative multi-robot systems, through flocking control in particular, improving their self-adaptive and self-learning abilities. This review is conducted to gain extensive knowledge related to swarming, or cluster flocking. The evolution of flocking laws from inception is delineated, swarming/cluster flocking is conceptualized, and the flocking phenomenon in multi-robots is evaluated. The taxonomy of flocking control based on different schemes, structures, and strategies is presented. Flocking control based on traditional and trending approaches, as well as hybrid control paradigms, is observed to elevate the robustness and performance of multi-robot systems for collective motion. Opportunities for deploying robots with flocking control in various domains are also discussed. Some challenges are also explored, requiring future considerations. Finally, the flocking problem is defined and an abstraction of flocking control-based multiple UAVs is presented by leveraging the potentials of various methods. The significance of this review is to inspire academics and practitioners to adopt multi-robot systems with flocking control for swiftly performing tasks and saving energy. Full article
(This article belongs to the Special Issue Advanced Control and Path Planning of Unmanned Aerial Vehicles (UAVs))
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