Control, Planning, and Embodied Intelligence of Agile UAVs in Indoor Environments

A special issue of Drones (ISSN 2504-446X).

Deadline for manuscript submissions: 30 December 2025 | Viewed by 2

Special Issue Editors


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Guest Editor
Nanyang Environment and Water Research Institute, Nanyang Technological University, Singapore 637141, Singapore
Interests: learning-based control for UAVs; UAV applications in industrial scenarios; reinforcement learning; model predictive control
School of Astronautics, Harbin Institute of Technology, Harbin 150001, China
Interests: hybrid terrestrial/aerial bicopters; planning and control for specialized UAVs; hybrid systems control

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Guest Editor
Department of Electrical and Computer Engineering, National University of Singapore, Singapore 117583, Singapore
Interests: control theory, optimization, and machine learning with applications for UAVs

Special Issue Information

Dear Colleagues,

Unmanned aerial vehicles (UAVs) operating in confined indoor spaces represent one of the most demanding frontiers in autonomous robotics. Unlike open outdoor environments, indoor settings often present GPS-denied conditions, complex geometry, dynamic obstacles, and tight maneuvering constraints. To ensure fast, safe, and reliable navigation under such conditions, UAVs must integrate high-performance control, agile motion planning, and tightly coupled perception and decision-making modules—hallmarks of embodied intelligence.

Advancing autonomous flight in these scenarios requires addressing several intertwined challenges: precise state estimation without external localization systems, real-time obstacle avoidance at high velocity, robust control under aerodynamic disturbances and close-quarters dynamics, and the ability to perceive and adapt to cluttered, dynamic environments. Emerging methods that blend model-based control with learning-based planning, visual–inertial odometry, and onboard sensor fusion are pushing the limits of what is possible for agile UAV flight indoors.

This Special Issue will gather the latest research on enabling agile UAVs to navigate complex indoor environments with minimal human intervention. We seek contributions that explore fundamental theory, algorithmic innovation, system integration, and experimental validation. Studies demonstrating end-to-end autonomy on resource-constrained platforms are especially welcome.

This Special Issue will welcome manuscripts related to the following themes:

  • Agile flight control and disturbance rejection in constrained spaces;
  • Perception-aware motion planning and trajectory optimization;
  • Vision-based navigation and state estimation in GPS-denied environments;
  • Learning-based policies for navigation and control (e.g., imitation learning, reinforcement learning);
  • Integration of perception, control, and planning for real-time operation;
  • Collision avoidance and environment interaction at high speeds;
  • Design of lightweight, high-performance UAV platforms for indoor use;
  • Embodied intelligence and sensorimotor coupling in autonomous UAVs.

We look forward to receiving your original research articles and reviews.

Dr. Minghao Han
Dr. Bo Cai
Dr. Lin Zhao
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

  • autonomous guidance and navigation
  • agile UAVs
  • indoor navigation
  • agile control
  • perception-aware planning
  • embodied intelligence

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Published Papers

This special issue is now open for submission.
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