Test Methodologies for Collision Tolerance, Navigation, and Trajectory-Following Capabilities of Small Unmanned Aerial Systems
SmallUnmanned Aerial Systems (sUAS) have seen rapid adoption thanks to advances in endurance, communications, autonomy, and manufacturing costs, yet most testing remains focused on GPS-supported, above-ground operations. This study introduces new test methodologies and presents comprehensive experimental evaluations of collision tolerance, navigation, and trajectory following for commercial sUAS platforms in GPS-denied indoor environments. We also propose numerical and categorical metrics—based on established vehicle collision protocols such as the Modified Acceleration Severity Index (MASI) and Maximum Delta V (MDV)—to quantify collision resilience; for example, the tested platforms achieved an average MASI of 0.1 g, while demonstrating clear separation between the highest- and lowest-performing systems. The experimental results revealed that performance varied significantly with mission complexity, obstacle proximity, and trajectory requirements, identifying platforms best suited for subterranean or crowded indoor applications. By aggregating these metrics, users can select the optimal drone for their specific mission requirements in challenging enclosed spaces.
Authors
- Edwin Meriaux (ORCID: https://orcid.org/0000-0002-9186-5362)
- Kshitij Jerath (ORCID: https://orcid.org/0000-0001-6356-9438)
Institutions
- University of Massachusetts Lowell (US)
Publication Details
- Journal
- Drones
- Published
- 2025-06-18
- DOI
- https://doi.org/10.3390/drones9060447
- Primary Topic
- Robotic Path Planning Algorithms
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- U.S. Army Combat Capabilities Development Command Soldier Center