Scaling Autonomous Flight: Coordinating Mechanics, Edge AI, and Policy to Surpass Energy and Swarm Limits
Abstract: Small autonomous drones have moved from prototypes to operational assets, yet research and deployment remain fragmented across mechanical, computational, and regulatory silos. This paper delivers a systems?level synthesis that unites these strands and quantifies their interaction on performance. We apply a three?phase methodology: (i) comparative case studies of mature deployments in medical logistics, ecological restoration, and public entertainment; (ii) parametric trade?off modelling that links air?frame mass, battery energy density, compute load, and mesh latency to range and payload; and (iii) causal?loop analysis. Six findings emerge: 1) order?of?magnitude gains in speed and coverage; 2) a 300?Wh?kg?? energy ceiling that restricts long?range BVLOS missions; 3) compute mass and packet loss jointly capping swarms at ?300 units; 4) a feedback loop tying power, connectivity, and cyber?security; 5) fragmented BVLOS and Remote?ID rules inflating costs and delays; and 6) community acceptance driven by demonstrated benefit and sub?45?dB acoustic profiles. Empirical data spanning over a million sorties and thousands of synchronized flight?hours ground the analysis. Isolated optimisation simply migrates bottlenecks; only coordinated advances across energy, edge intelligence, networking, and policy can unlock the next performance tier. The paper closes with a staged roadmap to scale autonomous flight into resilient, equitable infrastructure.
Keywords: Autonomous drones, Edge AI, Energy?density limits, Swarm robotics, BVLOS regulation
How to Cite?: Aryan Mittal, "Scaling Autonomous Flight: Coordinating Mechanics, Edge AI, and Policy to Surpass Energy and Swarm Limits", Volume 14 Issue 8, August 2025, International Journal of Science and Research (IJSR), Pages: 446-450, https://www.ijsr.net/getabstract.php?paperid=SR25729120734, DOI: https://dx.doi.org/10.21275/SR25729120734