SimuDrones: A Browser-Based 3D Virtual Laboratory for Drone Design, Rule-Based Hardware Validation, and Physics-Simulated Flight

Abstract Purpose: Existing drone simulation environments address flight physics or component configuration in isolation and typically demand complex local installation , dedicated hardware, and expert-level setup. No unified, browser-accessible platform covers the complete engineering workflow from part selection and three-dimensional assembly to electrical wiring and physics-based test flight. This work presents SimuDrones, which closes that gap for educational settings. Methods: SimuDrones is structured in four layers: (i) a structured component database encoding real-world electrical and mechanical specifications for motors, ESCs, batteries, propellers, and flight controllers; (ii) a WebGL-based 3D assembly environment built on React Three Fiber and Zustand; (iii) a sequential 19-rule hardware-compatibility validation engine; and (iv) a real-time Euler-integration physics flight simulator that derives all force parameters directly from the user-assembled drone specification. An interactive node-graph circuit builder covers three professional flight controllers. The system is implemented as a Next.js 16 web application requiring zero local installation. Results: Controlled evaluation across 47 curated build configurations— covering correct builds, single-fault injections across all 19 rule categories, and compound multi-fault cases—achieved 100% precision and recall. The Euler-integration hover-throttle model deviated by at most ±4.2% from the Newtonian analytical ground truth across five drone weight classes (200 g to 1400 g), with propeller spin-up/spin-down dynamics yielding R 2 = 0.97. Application load time averaged 2.8 s on broadband hardware at a stable 60 fps render rate. 1 Conclusion: SimuDrones constitutes the first unified, zero-installation browser platform integrating 3D drone assembly, automated hardware validation, interactive flight-controller wiring, and physics-based flight simulation, offering an engineering-grade educational tool for university drone curricula and online learning environments.

Authors

Publication Details

Journal
Research Square
Published
2026-11-09
DOI
https://doi.org/10.21203/rs.3.rs-10042500/v1
Primary Topic
Experimental Learning in Engineering
Type
preprint
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preprint

SimuDrones: A Browser-Based 3D Virtual Laboratory for Drone Design, Rule-Based Hardware Validation, and Physics-Simulated Flight

Jayesh Ambekar, Pranjal Batiya, Suchita Jadhav
Research Square
Experimental Learning in Engineering
preprint

SimuDrones: A Browser-Based 3D Virtual Laboratory for Drone Design, Rule-Based Hardware Validation, and Physics-Simulated Flight

Jayesh Ambekar, Pranjal Batiya, Suchita Jadhav
preprint en

Abstract

Abstract Purpose: Existing drone simulation environments address flight physics or component configuration in isolation and typically demand complex local installation , dedicated hardware, and expert-level setup. No unified, browser-accessible platform covers the complete engineering workflow from part selection and three-dimensional assembly to electrical wiring and physics-based test flight. This work presents SimuDrones, which closes that gap for educational settings. Methods: SimuDrones is structured in four layers: (i) a structured component database encoding real-world electrical and mechanical specifications for motors, ESCs, batteries, propellers, and flight controllers; (ii) a WebGL-based 3D assembly environment built on React Three Fiber and Zustand; (iii) a sequential 19-rule hardware-compatibility validation engine; and (iv) a real-time Euler-integration physics flight simulator that derives all force parameters directly from the user-assembled drone specification. An interactive node-graph circuit builder covers three professional flight controllers. The system is implemented as a Next.js 16 web application requiring zero local installation. Results: Controlled evaluation across 47 curated build configurations— covering correct builds, single-fault injections across all 19 rule categories, and compound multi-fault cases—achieved 100% precision and recall. The Euler-integration hover-throttle model deviated by at most ±4.2% from the Newtonian analytical ground truth across five drone weight classes (200 g to 1400 g), with propeller spin-up/spin-down dynamics yielding R 2 = 0.97. Application load time averaged 2.8 s on broadband hardware at a stable 60 fps render rate. 1 Conclusion: SimuDrones constitutes the first unified, zero-installation browser platform integrating 3D drone assembly, automated hardware validation, interactive flight-controller wiring, and physics-based flight simulation, offering an engineering-grade educational tool for university drone curricula and online learning environments.

Research Square
Experimental Learning in Engineering
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