Pseudo-Random UAV Test Generation Using Low-Fidelity Path Simulator

Fuente: arXiv
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Autores principales: Shrinah, Anas, Eder, Kerstin
Formato: Preprint
Publicado: 2025
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author Shrinah, Anas
Eder, Kerstin
author_facet Shrinah, Anas
Eder, Kerstin
contents Simulation-based testing provides a safe and cost-effective environment for verifying the safety of Uncrewed Aerial Vehicles (UAVs). However, simulation can be resource-consuming, especially when High-Fidelity Simulators (HFS) are used. To optimise simulation resources, we propose a pseudo-random test generator that uses a Low-Fidelity Simulator (LFS) to estimate UAV flight paths. This work simplifies the PX4 autopilot HFS to develop a LFS, which operates one order of magnitude faster than the HFS.Test cases predicted to cause safety violations in the LFS are subsequently validated using the HFS.
format Preprint
id arxiv_https___arxiv_org_abs_2503_24172
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Pseudo-Random UAV Test Generation Using Low-Fidelity Path Simulator
Shrinah, Anas
Eder, Kerstin
Robotics
Simulation-based testing provides a safe and cost-effective environment for verifying the safety of Uncrewed Aerial Vehicles (UAVs). However, simulation can be resource-consuming, especially when High-Fidelity Simulators (HFS) are used. To optimise simulation resources, we propose a pseudo-random test generator that uses a Low-Fidelity Simulator (LFS) to estimate UAV flight paths. This work simplifies the PX4 autopilot HFS to develop a LFS, which operates one order of magnitude faster than the HFS.Test cases predicted to cause safety violations in the LFS are subsequently validated using the HFS.
title Pseudo-Random UAV Test Generation Using Low-Fidelity Path Simulator
topic Robotics
url https://arxiv.org/abs/2503.24172