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Drones
Special Issues
From Nature to Flight: Bio-Inspired UAV Design and Intelligence
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From Nature to Flight: Bio-Inspired UAV Design and Intelligence

A Special Issue of Drones (ISSN 2504-446X) belonging to the section "Drone Design and Development".

Deadline for manuscript submissions: closed (15 April 2026) | Viewed by 1225

Editors

Dr. Chahat Deep Singh

E-Mail Website
Guest Editor
Perception, Robotics, AI and Sensing Lab, University of Colorado, Boulder, CO 80309, USA
Interests: drone autonomy; minimal perception and computer vision
Dr. J. Sean Humbert

E-Mail Website
Guest Editor
Department of Mechanical Engineering, University of Colorado, Boulder, CO 80309, USA
Interests: autonomous navigation; UAS flight mechanics; control; system identification; bio-inspired sensory processing
Dr. Kaushik Jayaram

E-Mail Website
Guest Editor
1. Department of Mechanical Engineering, University of Colorado Boulder, Boulder, CO, USA
2. Department of Bioengineering, Imperial College London, London, UK
Interests: bioinspired robotics; biomechanics; micromanufacturing

Special Issue Information

Dear Colleagues,

Unmanned aerial vehicles (UAVs) have become indispensable tools in diverse domains, ranging from environmental monitoring and precision agriculture to disaster response and defense applications. While remarkable progress has been made in control algorithms, sensing, and design, UAVs still face fundamental challenges in achieving robust autonomy, energy efficiency, and adaptability in complex environments. Nature offers a wealth of inspiration for addressing these challenges, as biological systems exhibit unparalleled efficiency, resilience, and intelligence. By drawing on bio-inspired principles—such as neuromorphic intelligence, flapping-wing locomotion, swarm intelligence, parsimonious perception and control, and adaptive morphology—researchers can develop UAVs that transcend current technological limitations.

The goal of this Special Issue is to collect papers (original research articles and review papers) to give insights about bio-inspired approached to UAV autonomy and design. By bridging robotics, biology, perception, artificial intelligence and control systems, this Special Issue seeks to advance the next generation of UAV technologies and provide a platform for interdisciplinary contributions that align with the journal’s scope in advancing innovative UAV research and applications.

This Special Issue will welcome manuscripts in a wide range of topics including, but not limited to, the following:

  • Bio-inspired autonomy, including perception, navigation, and decision-making.
  • Flight mechanisms, morphologies, and design derived from nature.
  • Energy efficiency in bio-inspired UAVs
  • Bio-inspired collective and swarm behaviors for multi-UAV systems.
  • Neuromorphic sensors, processing and integration.

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

Dr. Chahat Deep Singh
Dr. J. Sean Humbert
Dr. Kaushik Jayaram
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 250 words) can be sent to the Editorial Office for assessment.

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-anonymized 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

  • bio-inspired UAVs
  • aerial robotics
  • drone autonomy
  • energy-efficient UAVs
  • swarm intelligence
  • neuromorphic perception and control

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

Published Papers (1 paper)

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Research

34 pages, 7005 KB  
Article
Data Acquisition with Optical and Force Sensors for an Eagle-Shaped Ornithopter
by Alejandro Ramos, Ahmad Hammad and Sophie F. Armanini
Drones 2026, 10(6), 411; https://doi.org/10.3390/drones10060411 - 26 May 2026
Viewed by 624
Abstract
This paper presents the process of gathering data for a flapping-wing micro air vehicle (FWMAV) using optical tracking and force sensors for subsequent dynamic modeling and simulation purposes. Tethered and clamped experiments were performed to track the vehicle’s overall motion, wing kinematic angles, [...] Read more.
This paper presents the process of gathering data for a flapping-wing micro air vehicle (FWMAV) using optical tracking and force sensors for subsequent dynamic modeling and simulation purposes. Tethered and clamped experiments were performed to track the vehicle’s overall motion, wing kinematic angles, and aerodynamic force patterns, while additional properties such as mass, inertia tensor, center-of-mass position, and short-period excitation frequency were also examined. The methodology includes the testing approaches, modeling choices, and error analyses applied to the measurements. The results demonstrate that both tethered and clamped configurations introduce key limitations, particularly for steady-state flight. Additional constraints include structural fragility (hindering high-frequency testing), over-simplified CAD geometry, and controller tuning issues on the tail. Based on the identified parameters and experimental datasets, a high-fidelity simulation model was developed in MATLAB to serve as a platform for future control and flight envelope studies. Overall, the combination of optical tracking and force sensing provides a structured framework for linking experimental data to physical models, laying the foundation for future improvements in ornithopter modeling and testing. Full article
(This article belongs to the Special Issue From Nature to Flight: Bio-Inspired UAV Design and Intelligence)
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