Mission Planning, Perception and Control for Drones in Wide-Area Operations

A special issue of Drones (ISSN 2504-446X). This special issue belongs to the section "Drone Design and Development".

Deadline for manuscript submissions: 31 January 2025 | Viewed by 1291

Special Issue Editors

Department of Control Science and Engineering, Harbin Institute of Technology, Harbin 150001, China
Interests: multi-agent systems; path planning and decision; state estimation
Special Issues, Collections and Topics in MDPI journals

E-Mail Website
Guest Editor
Department of Control Science and Engineering, Harbin Institute of Technology, Harbin, China
Interests: dynamic control of drones; adaptive control; intelligent perception

E-Mail Website
Guest Editor
School of Computer Engineering and Science, Shanghai University, Shanghai, China
Interests: internet of things analytics; embodied intelligence; robotic technology

E-Mail Website
Guest Editor
School of Computer Engineering and Science, Shanghai University, Shanghai, China
Interests: robotics

E-Mail Website
Guest Editor
Department of Cognitive Robotics, Faculty of Mechanical Engineering, Delft University of Technology, Delft, The Netherlands
Interests: robotics; optimal control; reinforcement learning

Special Issue Information

Dear Colleagues,

Drones are playing an increasingly important role in both military and civilian fields, especially in wide-area operations. The closed loop, consisting of mission planning, perception, and control, is the key technology to achieve high-level intelligent autonomous wide-area operating drones. Establishing a sophisticated architecture, coordinating the components’ relationships, and achieving information interconnection are essential for reliability and performance of this loop, which brings tremendous emphasis on swarming intelligent, formation planning, control safety, etc.

This Special Issue, entitled Mission Planning, Perception, and Control for Drones in Wide-area Operations, aims to provide a scientific platform regarding the new trends in technologies for drones in wide-area operations, including mission planning technology, artificial intelligence, autonomous intelligent unmanned systems, and the combination of learning and control. We would like to collect innovative research including but not limited to mission planning, reliable perception, decision making, machine learning, and control.

Review and Original Research articles are welcome. Topics of interests include, but are not limited to, the following:

1) Motion control and path planning for wide-area operating drones;

2) Mission planning for wide-area operating drones;

3) Task decomposition and allocation for wide-area operating drones;

4) Simultaneous localization and mapping in a complex environment;

5) Vision recognition and detection;

6) Intelligent perception techniques;

7) Model-based predictive control for intelligent systems;

8) Robust control, sliding mode control, and adaptive control;

9) Deep learning and reinforcement learning;

10) Architecture for learning and control integration;

11) Advanced decision and control methods for unmanned systems;

12) Intelligent swarm and formation.

We look forward to receiving your contributions.

Dr. Weiran Yao
Dr. Xiangyu Shao
Dr. Yuehua Liu
Prof. Dr. Liming Xin
Dr. Jiatao Ding
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. Drones 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 2600 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

  • motion control and path planning for wide-area operating drones
  • mission planning for wide-area operating drones
  • task decomposition and allocation for wide-area operating drones
  • simultaneous localization and mapping in a complex environment
  • vision recognition and detection
  • intelligent perception techniques
  • model-based predictive control for intelligent systems
  • robust control, sliding mode control, and adaptive control
  • deep learning and reinforcement learning
  • architecture for learning and control integration
  • advanced decision and control methods for unmanned systems
  • intelligent swarm and formation

Benefits of Publishing in a Special Issue

  • Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
  • Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
  • Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
  • 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 polices can be found here.

Published Papers (1 paper)

Order results
Result details
Select all
Export citation of selected articles as:

Research

20 pages, 2951 KiB  
Article
R-LVIO: Resilient LiDAR-Visual-Inertial Odometry for UAVs in GNSS-denied Environment
by Bing Zhang, Xiangyu Shao, Yankun Wang, Guanghui Sun and Weiran Yao
Drones 2024, 8(9), 487; https://doi.org/10.3390/drones8090487 - 14 Sep 2024
Viewed by 959
Abstract
In low-altitude, GNSS-denied scenarios, Unmanned aerial vehicles (UAVs) rely on sensor fusion for self-localization. This article presents a resilient multi-sensor fusion localization system that integrates light detection and ranging (LiDAR), cameras, and inertial measurement units (IMUs) to achieve state estimation for UAVs. To [...] Read more.
In low-altitude, GNSS-denied scenarios, Unmanned aerial vehicles (UAVs) rely on sensor fusion for self-localization. This article presents a resilient multi-sensor fusion localization system that integrates light detection and ranging (LiDAR), cameras, and inertial measurement units (IMUs) to achieve state estimation for UAVs. To address challenging environments, especially unstructured ones, IMU predictions are used to compensate for pose estimation in the visual and LiDAR components. Specifically, the accuracy of IMU predictions is enhanced by increasing the correction frequency of IMU bias through data integration from the LiDAR and visual modules. To reduce the impact of random errors and measurement noise in LiDAR points on visual depth measurement, cross-validation of visual feature depth is performed using reprojection error to eliminate outliers. Additionally, a structure monitor is introduced to switch operation modes in hybrid point cloud registration, ensuring accurate state estimation in both structured and unstructured environments. In unstructured scenes, a geometric primitive capable of representing irregular planes is employed for point-to-surface registration, along with a novel pose-solving method to estimate the UAV’s pose. Both private and public datasets collected by UAVs validate the proposed system, proving that it outperforms state-of-the-art algorithms by at least 12.6%. Full article
Show Figures

Figure 1

Back to TopTop