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Predicting Technological Trends and Effects Enabling Large-Scale Supply Drones

Submitted:

19 December 2025

Posted:

22 December 2025

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Abstract
Drones have long been explored for supply. While several systems offering small pay-loads in drone delivery have seen operational use, large-scale supply drones have yet to be adopted. A range of setbacks cause this, including technological and operational challenges that hinder their adoption. Here, these challenges are evaluated from a conceptual modelling perspective to forecast their applicability once these barriers are overcome. The study uses technology trend modelling and bibliometric activity map-ping methodologies to predict the applicability of specific technologies that are cur-rently identified as operational challenges. Specifically for supply drones, trends in technological improvements of battery technology and aircraft control are modelled to project effects and focus on landing zone autonomy and powertrain. The prediction also focuses on the current state of hybrid power and higher levels of automation required for landing zone operations. These models are validated through several published case studies of small delivery drones and then applied to assess the feasibility and con-straints of larger supply drones. A case study, conceptual design of a supply drone large enough to move a shipping container, is presented to illustrate the critical technologies required to transition large supply drones from concept to operational reality. Key technologies required for large-scale supply drones have yet to build up a critical mass of research activity, particularly on landing zone autonomy and powertrain. Moreover, additional constraints beyond technological and operational challenges could include limitations in autonomy, certification hurdles, regulatory complexity, and the need for greater social trust and acceptance.
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Copyright: This open access article is published under a Creative Commons CC BY 4.0 license, which permit the free download, distribution, and reuse, provided that the author and preprint are cited in any reuse.
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