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Robotics
Special Issues
Aerial Robotics and Applications of UAS
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Aerial Robotics and Applications of UAS

A special issue of Robotics (ISSN 2218-6581). This special issue belongs to the section "Aerospace Robotics and Autonomous Systems".

Deadline for manuscript submissions: closed (31 May 2023) | Viewed by 4246

Special Issue Editors

Dr. Hakki Erhan Sevil

E-Mail Website
Guest Editor
Department of Intelligent Systems & Robotics, University of West Florida, Pensacola, FL 32514, USA
Interests: cyber security; intelligent systems; guidance-navigation-control of unmanned vehicles; multi-agent systems; robotics; data-driven detection and estimation; computer vision
Special Issues, Collections and Topics in MDPI journals
Dr. Liang Sun

E-Mail Website
Guest Editor
Department of Mechanical & Aerospace Engineering, New Mexico State University, Las Cruces, NM 88003, USA
Interests: drones; unmanned aerial/ground vehicles; tethered UAV systems; task allocation; sound source localization; optimal sensor management; cooperative control and estimation

Special Issue Information

Dear Colleagues,

Recent advances in aerial robotics and unmanned aircraft systems (UASs) make it feasible to deploy aerial platforms for tasks such as search and rescue, disaster response, and surveillance. As UASs have significant advantages over ground platforms, it is rational to implement them, as they can reach the desired locations relatively easier considering tough terrain conditions and complex obstacles. When it comes to a mission such as search and rescue that requires covering large areas, or natural disasters response, UAS will function in a timely, cost efficient, and more effective way than other platform types.

This Special Issue is dedicated to bring current research on aerial robotics and UAS applications, including:

  • Mathematical basics used in aerial robotics;
  • Algorithmic principles underlying autonomous navigation of aerial robots;
  • Aerial robotics sections; sensors, navigation, path planning, control, and localization;
  • UAS applications such as:
    • Search and rescue;
    • Monitoring disaster areas;
    • Precision agriculture − crop monitoring;
  • Current trends in aerial robotics.

We welcome both original papers and reviews that provide in depth knowledge with the most recent advancements in all aspects of Aerial Robotics and UAS applications.

Dr. Hakki Erhan Sevil
Dr. Liang Sun
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. Robotics 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 1800 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.

Keywords

  • aerial robotics
  • unmanned aircraft systems (UAS)
  • unmanned aerial vehicle (UAV)
  • UAS applications
  • localization and mapping in aerial robotics
  • perception in aerial robotics
  • planning in aerial robotics

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Published Papers (1 paper)

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Research

32 pages, 18847 KiB  
Article
Perception, Path Planning, and Flight Control for a Drone-Enabled Autonomous Pollination System
by Chapel Reid Rice, Spencer Thomas McDonald, Yang Shi, Hao Gan, Won Suk Lee, Yang Chen and Zhenbo Wang
Robotics 2022, 11(6), 144; https://doi.org/10.3390/robotics11060144 - 5 Dec 2022
Cited by 4 | Viewed by 3388
Abstract
The decline of natural pollinators necessitates the development of novel pollination technologies. In this work, we propose a drone-enabled autonomous pollination system (APS) that consists of five primary modules: environment sensing, flower perception, path planning, flight control, and pollination mechanisms. These modules are [...] Read more.
The decline of natural pollinators necessitates the development of novel pollination technologies. In this work, we propose a drone-enabled autonomous pollination system (APS) that consists of five primary modules: environment sensing, flower perception, path planning, flight control, and pollination mechanisms. These modules are highly dependent upon each other, with each module relying on inputs from the other modules. In this paper, we focus on approaches to the flower perception, path planning, and flight control modules. First, we briefly introduce a flower perception method from our previous work to create a map of flower locations. With a map of flowers, APS path planning is defined as a variant of the Travelling Salesman Problem (TSP). Two path planning approaches are compared based on mixed-integer programming (MIP) and genetic algorithms (GA), respectively. The GA approach is chosen as the superior approach due to the vast computational savings with negligible loss of optimality. To accurately follow the generated path for pollination, we develop a convex optimization approach to the quadrotor flight control problem (QFCP). This approach solves two convex problems. The first problem is a convexified three degree-of-freedom QFCP. The solution to this problem is used as an initial guess to the second convex problem, which is a linearized six degree-of-freedom QFCP. It is found that changing the objective of the second convex problem to minimize the deviation from the initial guess provides improved physical feasibility and solutions similar to a general-purpose optimizer. The path planning and flight control approaches are then tested within a model predictive control (MPC) framework where significant computational savings and embedded adjustments to uncertainty are observed. Coupling the two modules together provides a simple demonstration of how the entire APS will operate in practice. Full article
(This article belongs to the Special Issue Aerial Robotics and Applications of UAS)
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