Unmanned Aerial Manipulation with Physical Interaction
A special issue of Drones (ISSN 2504-446X). This special issue belongs to the section "Drone Design and Development".
Deadline for manuscript submissions: 20 November 2025 | Viewed by 620
Special Issue Editors
Interests: unmanned aerial vehicles; aerial manipulator; geometric control; active vision; robot learning; mechatronic system design; software development for self-driving vehicles
Special Issue Information
Dear Colleagues,
Traditional aerial vehicles have primarily been used as observation platforms. However, the field is rapidly evolving as physical interactions using unmanned aerial vehicles become more prevalent. Unmanned aerial manipulators represent a significant advancement in robotics, enabling aerial robots to transition from merely observing the environment to actively interacting with it. This evolution greatly enhances the mobility and operational range of traditional manipulators, positioning them as the "next generation of aerial robots". They hold promising potential for applications in high-rise building inspections, teleoperation, and logistics.
Despite these advancements, several critical challenges remain in the physical interaction of unmanned aerial vehicles. Traditional unmanned aerial vehicles are typically under-actuated, which makes it difficult to perform tasks requiring physical interaction. In recent years, various fully actuated unmanned aerial platforms have been developed specifically for these purposes. However, efficient design methodologies for unmanned aerial vehicles under physical interaction are still an ongoing challenge that warrants further research. Unlike unmanned ground vehicles, unmanned aerial vehicles are more susceptible to environmental disturbances such as wind, which adds complexity to control problems. Therefore, developing effective control strategies is crucial but challenging. Localization is also a key issue; improving the accuracy of unmanned aerial vehicles during interactions can greatly enhance their effectiveness.
Reinforcement learning has emerged as a valuable tool for improving the performance and robustness of autonomous vehicles. State-of-the-art reinforcement learning algorithms can potentially benefit the development of physical interaction policies for unmanned aerial vehicles, enabling them to adapt to complex and dynamic environments.
The goal of this Special Issue is to collect papers (original research articles and review papers) to give insights about physical interaction using unmanned aerial vehicles. Papers addressing key challenges and critical issues related to these topics are especially welcome.
This Special Issue will welcome manuscripts that link, but are not limit to, the following themes:
- Design of unmanned aerial platforms for physical interaction.
- Interaction control of unmanned aerial vehicles.
- Cooperative unmanned aerial manipulation and transportation.
- Localization of unmanned aerial vehicles under physical interaction.
- Physical interaction between human and unmanned aerial vehicles
- Unmanned aerial manipulation via reinforcement learning.
- Simulation of unmanned aerial vehicles under physical interaction.
We look forward to receiving your original research articles and reviews.
Dr. Yushu Yu
Prof. Dr. Vincenzo Lippiello
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
- unmanned aerial manipulation
- cooperative unmanned aerial transportation
- fully actuated unmanned aerial vehicle
- interaction control
- human–robot interaction
- localization
- reinforcement learning
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.
- Reprint: MDPI Books provides the opportunity to republish successful Special Issues in book format, both online and in print.
Further information on MDPI's Special Issue policies can be found here.
